SYSTEM AND METHOD FOR IMPROVING THE PERFORMANCE OF VEHICLE MOTION CONTROL USING REAL-TIME DATA TO ASSESS RELIABILITY AND CRITICALITY

Abstract

System (10) for improving the performance of vehicle motion control using real-time data to assess reliability and criticality, wherein the system (10) comprises: a vehicle (12); a plurality of sensors (70) arranged on the vehicle (12) and collecting real-time information about a dynamic state of the vehicle (12); a plurality of actuators (30, 44) arranged on the vehicle (12) and actively and continuously adjusting the dynamic state of the vehicle (12);a controller (50) comprising a processor (52), a memory (54) and one or more input / output (I / O) ports (56), wherein the I / O ports (56) communicate with the plurality of sensors (70) and the plurality of actuators (30, 44), wherein the processor (52) executes programmatic control logic stored in the memory (54), wherein the programmatic control logic includes an application for improving the performance of the vehicle motion control (VMC) (92), wherein the VMC application (92) comprises: a first control logic for obtaining real-time information about the dynamic state of the vehicle (12) from the plurality of sensors (70) and from the plurality of actuators (30, 44); a second control logic for estimating a dynamic real-time vehicle state from the information about the dynamic state of the vehicle (12);a third control logic for determining signal criticality and signal reliability for information about the dynamic state of the vehicle (12); a fourth control logic for executing a VMC strategy based on the dynamic state of the vehicle (12) in real time, the signal criticality, and the signal reliability; a fifth control logic for detecting and mitigating signal degradation by selectively applying one or more alternative VMC strategies; and a sixth control logic for generating a VMC output command to the plurality of actuators (30, 44) based on the VMC strategy, wherein the VMC strategy actively, continuously, and automatically adapts to seamlessly overcome signal degradation;characterized in that the third control logic is further configured to: determine the signal criticality based on the signal sensitivity, the actuator effectiveness of relevant actuators (30, 44) of the plurality of actuators (30, 44) and the importance of associated performance metrics (230) in real time, wherein the signal sensitivity is a measure of how dependent the control logic for a particular actuator (30, 44) is on an associated control signal, wherein the actuator effectiveness is a measure of the effectiveness of an associated control logic that controls the particular actuators (30, 44) relative to a specific performance index, and wherein the importance of associated performance metrics (230) defines a necessity of the associated performance metric (230) at a particular time in real time;and wherein signal criticality is defined as the sum of the sensitivities of control methods to an input signal, multiplied by the sum of the effectiveness of control methods for a vehicle performance metric (230), multiplied by the importance of performance metrics (230) in real time.

Description

INTRODUCTION

[0001] The present disclosure relates to vehicle motion control, and more particularly, to systems and methods for monitoring the condition and deterioration of vehicle motion control system components. Vehicle motion control systems are becoming increasingly complex, as many are increasingly computer-controlled and operated. Various subsystems of vehicle motion control systems work in complex harmony to control vehicle performance. In many cases, multiple vehicle motion control subsystems can be employed to alter vehicle performance and achieve the same result. However, managing such complex interactions between multiple subsystems can result in uncertainty and reduced effectiveness of any individual control action taken to achieve an overall vehicle motion control objective or performance function.

[0002] While current vehicle motion control systems and methods serve their purpose, there is a need for a new and improved vehicle motion control system and method that provides a robust, redundant, and reliable means of achieving an optimal vehicle motion control result, while providing health monitoring and degradation mitigation for multi-actuation, multi-target vehicle motion control, and while providing a means of determining input signal criticality and monitoring and generating performance metrics for vehicle motion control subsystems in real time without increasing manufacturing complexity, while utilizing existing hardware and enhancing the customer experience. SUMMARY

[0003] According to several aspects of the present disclosure, a system for improving vehicle motion control performance using real-time data for reliability and criticality assessments includes a vehicle, a plurality of sensors disposed on the vehicle, and a plurality of actuators disposed on the vehicle. The plurality of sensors collect information about a dynamic state of the vehicle in real time. The plurality of actuators actively and continuously adjust the dynamic state of the vehicle. The system further includes a controller having a processor, a memory, and one or more input / output (I / O) ports. The I / O ports communicate with the plurality of sensors and the plurality of actuators. The processor executes programmatic control logic stored in memory. The programmatic control logic includes a vehicle motion control (VMC) performance improvement application.The VMC application includes at least first, second, third, fourth, fifth, and sixth control logic portions. The first control logic receives real-time information about the dynamic state of the vehicle from the plurality of sensors and the plurality of actuators. The second control logic estimates the dynamic state of the vehicle in real time based on the dynamic state information. The third control logic determines a signal criticality and a signal reliability for information about the dynamic state of the vehicle. The fourth control logic executes a VMC strategy based on the real-time dynamic state of the vehicle, the signal criticality, and the signal reliability. The fifth control logic detects and mitigates signal degradation by selectively applying one or more alternative VMC strategies.The sixth control logic generates a VMC output command for the plurality of actuators based on the VMC strategy. The VMC strategy actively, continuously, and automatically adapts to seamlessly overcome signal degradation.

[0004] In another aspect of the present disclosure, the second control logic further comprises measuring the position, motion, and acceleration of the vehicle in three or more degrees of freedom in real time with the plurality of sensors and the plurality of actuators. Each of the real-time dynamic state estimates defines a particular aspect of the dynamic state of the vehicle.

[0005] In another aspect of the present disclosure, the third control logic further comprises determining signal criticality based on signal sensitivity, actuator effectiveness of relevant actuators from the plurality of actuators, and the importance of associated real-time performance metrics. Signal sensitivity is a measure of how dependent the control logic for a particular actuator is on a corresponding control signal. Actuator effectiveness is a measure of the effectiveness of associated control logic controlling the individual actuators relative to a particular performance index, and the importance of associated real-time performance metrics defines a need for the associated performance metric at a particular time.Signal criticality defines the sum of the sensitivities of the control methods to an input signal, multiplied by the sum of the effectiveness of the control methods for a vehicle performance metric, multiplied by the importance of the performance metrics in real time.

[0006] In another aspect of the present disclosure, a vehicle performance metric is defined for each actuator configuration for the vehicle, such that the vehicle performance metric includes one of the following: a no-effect contribution to achieving a VMC goal; a limited-effectiveness contribution to achieving the VMC goal; and a highly effective contribution to achieving the VMC goal. High effectiveness is greater than limited effectiveness, and limited effectiveness is greater than the no-effect contribution to the VMC goal. Each actuator configuration makes a specific and unique contribution to each performance metric, and each actuator configuration defines a particular subset of actuators with which the vehicle is equipped and contributes to the VMC in a different way.

[0007] In another aspect of the present disclosure, the VMC application executes the fourth control logic based on the dynamic real-time vehicle state, signal criticality, and signal reliability and develops a VMC strategy related to the current VMC objectives and the effectiveness of the control methods with respect to the performance metrics and the associated VMC objectives. The VMC strategy establishes a ranking of the actuator control methods with respect to the current VMC objectives.

[0008] In another aspect of the present disclosure, the fifth control logic further comprises: control logic that actively, continuously, and automatically determines when the reliability of one or more input signals is equal to or below a predetermined reliability threshold for one or more input signals with a criticality equal to or above a predetermined criticality threshold.Upon determining that the reliability of the one or more input signals is equal to or below the predetermined reliability threshold and that the criticality of the one or more input signals is equal to or above the predetermined criticality threshold, active, continuous, and automatic adaptation is performed by using one or more alternative control methods with a reliability equal to or above the predetermined threshold for the criticality above the predetermined criticality threshold. If it is determined that the reliability of the one or more input signals is equal to or above the predetermined reliability threshold while the criticality is equal to or above the predetermined threshold, a control method with the highest ranking applicable to the current VMC objectives is used.

[0009] In another aspect of the present disclosure, the fifth control logic further comprises: control logic that determines that the reliability of the one or more input signals is equal to or below the predetermined reliability threshold, and that automatically switches the actuator control to one or more alternative actuator control methods that have less sensitivity to the one or more input signals that have been identified as less reliable than the predetermined reliability threshold compared to the highest ranked control method for application to the current VMC goals.

[0010] In another aspect of the present disclosure, the automatic transition between the highest-level control method and one or more alternative actuator control methods occurs automatically and instantaneously or automatically and stepwise.

[0011] In another aspect of the present disclosure, the sixth control logic further comprises: control logic for actively, continuously, and automatically executing a fusion degradation mitigation strategy that uses weighted averages of actuator control methods to define the VMC output command to the plurality of actuators. The VMC output command is calculated as follows: Weighting index of a control method = [∑Sensitivity of a control method to input signal ×∑Reliability of input signal] × [∑Effectiveness of control method against performance metric ×∑Importance of a performance metric in real time] so that: Last actuator control command = Weighting index of a control procedure × Output of control procedure Weighting index of a control procedure wherein the weighting index for an actuator control method is calculated by multiplying the sensitivity of the control method by the reliability of the input signal and by the effectiveness of the actuator control method for a given actuator control algorithm and further multiplied by the importance of a real-time performance metric.

[0012] In another aspect of the present disclosure, a method for improving vehicle motion control using real-time data reliability and criticality assessments includes collecting real-time information about a dynamic state of the vehicle using a plurality of sensors disposed on a vehicle. The method further includes actively and continuously adjusting a dynamic state of the vehicle using a plurality of actuators disposed on the vehicle.The method further comprises executing programmatic control logic including a vehicle motion control enhancement (VMC) application stored in memory of a controller of the vehicle, the controller having a processor, memory, and one or more input / output (I / O) ports, the I / O ports communicating with the plurality of sensors and the plurality of actuators. The VMC application includes control logic for: obtaining the real-time vehicle dynamic state information from the plurality of sensors and the plurality of actuators; estimating a real-time vehicle dynamic state based on the vehicle dynamic state information; and determining a signal criticality and a signal reliability for vehicle dynamic state information.The VMC application also includes control logic for: executing a VMC strategy based on the vehicle's real-time dynamic state, signal criticality, and signal reliability; detecting and mitigating signal degradation by selectively applying one or more alternative VMC strategies; and generating a VMC output command for the plurality of actuators based on the VMC strategy. The VMC strategy actively, continuously, and automatically adapts to seamlessly overcome signal degradation.

[0013] In another aspect of the present disclosure, the method further comprises measuring the position, motion, and acceleration of the vehicle in three or more degrees of freedom in real time with the plurality of sensors and the plurality of actuators. Each of the real-time dynamic state estimates defines a particular aspect of the dynamic state of the vehicle.

[0014] In another aspect of the present disclosure, the method further comprises determining signal criticality based on signal sensitivity, actuator effectiveness of relevant actuators from the plurality of actuators, and the real-time importance of associated performance metrics. Signal sensitivity is a measure of how dependent the control logic for a particular actuator is on a corresponding control signal. Actuator effectiveness is a measure of the effectiveness of associated control logic controlling the individual actuators relative to a particular performance index. The real-time importance of associated performance metrics defines a need for the associated performance metric at a particular time.Signal criticality defines the sum of the sensitivities of the control methods to an input signal, multiplied by the sum of the effectiveness of the control methods for a vehicle performance metric, multiplied by the importance of the associated performance metrics in real time.

[0015] In another aspect of the present disclosure, the method further comprises defining a vehicle performance metric for each actuator configuration for the vehicle such that the vehicle performance metric comprises one of the following: a no-effect contribution to achieving a VMC target; a limited-effectiveness contribution to achieving the VMC target; and a highly effective contribution to achieving the VMC target. The high effectiveness is greater than the limited effectiveness, and the limited effectiveness is greater than the no-effect contribution to the VMC target. Each actuator configuration makes a specific and unique contribution to each performance metric, and each actuator configuration defines a particular subset of actuators with which the vehicle is equipped and contributes to the VMC in a different way.

[0016] In another aspect of the present disclosure, the method further comprises developing a VMC strategy related to the current VMC goals and the effectiveness of the control methods relative to the performance metrics and associated VMC goals. The VMC strategy is based on the real-time dynamic state of the vehicle, signal criticality and reliability, and the ranking of the actuator control methods relative to the current VMC goals.

[0017] In another aspect of the present disclosure, the method further comprises actively, continuously, and automatically determining when a reliability of one or more input signals is equal to or below a predetermined reliability threshold for one or more input signals with a criticality equal to or above a predetermined criticality threshold. Upon determining that the reliability of the one or more input signals is equal to or below the predetermined reliability threshold and that the criticality of the one or more input signals is equal to or above the predetermined criticality threshold, active, continuous, and automatic adaptation is performed by using one or more alternative control methods with a reliability equal to or above the predetermined threshold for the criticality above the predetermined criticality threshold.If the reliability of the one or more input signals is determined to be equal to or above the predetermined reliability threshold while the criticality is equal to or above the predetermined threshold, a control method with the highest rank applicable to the current VMC objectives is used.

[0018] In another aspect of the present disclosure, the method further comprises determining that the reliability of the one or more input signals is equal to or below the predetermined reliability threshold, and automatically switching the actuator control to one or more alternative actuator control methods having a lower sensitivity to the one or more input signals identified as reliable and below the predetermined reliability threshold, compared to the highest ranked control method applicable to the current VMC objectives.

[0019] In another aspect of the present disclosure, the automatic transition between the highest-level control method and one or more alternative actuator control methods is one or more of the following: automatic and instantaneous or automatic and stepwise.

[0020] In another aspect of the present disclosure, the method further comprises actively, continuously, and automatically executing a fusion degradation mitigation strategy that uses weighted averages of actuator control methods to define the VMC output command for the plurality of actuators. The VMC output command is calculated as follows: Weighting index of a control method = [∑Sensitivity of a control method to input signal ×∑Reliability of input signal] × [∑Effectiveness of control method against performance metric ×∑Importance of a performance metric in real time] so that: Last actuator control command = Weighting index of a control procedure × Output of control procedure Weighting index of a control procedure wherein the weighting index for an actuator control method is calculated by multiplying the sensitivity of the control method by the reliability of the input signal and by the effectiveness of the actuator control method for a given actuator control algorithm and further multiplied by the importance of a real-time performance metric.

[0021] In another aspect of the present disclosure, a method for improving vehicle motion control performance using real-time data to evaluate reliability and criticality includes collecting real-time information about a dynamic state of the vehicle using a plurality of sensors disposed on a vehicle, actively and continuously adjusting a dynamic state of the vehicle using a plurality of actuators disposed on the vehicle, and executing programmatic control logic including a vehicle motion control improvement (VMC) application stored in a memory of a controller. The controller has a processor, a memory, and one or more input / output (I / O) ports. The I / O ports communicate with the plurality of sensors and the plurality of actuators.The VMC application with control logic includes obtaining real-time information about the dynamic state of the vehicle from the plurality of sensors and the plurality of actuators, including measuring, in real time, with the plurality of sensors and the plurality of actuators, a position, a motion, and an acceleration of the vehicle in three or more degrees of freedom. Each of the real-time estimates of the dynamic state defines a particular aspect of the dynamic state of the vehicle. The VMC application further includes control logic for estimating a real-time dynamic vehicle state from the dynamic state information of the vehicle and for determining a signal criticality and a signal reliability for the dynamic state information of the vehicle.Signal criticality is based on signal sensitivity, the actuator effectiveness of the relevant actuators from the multitude of actuators, and the importance of the associated real-time performance metrics. Signal sensitivity is a measure of how dependent the control logic for a specific actuator is on a corresponding control signal. Actuator effectiveness is a measure of the effectiveness of associated control logic that controls the individual actuators relative to a specific performance index, and the importance of associated real-time performance metrics defines a necessity for the performance metric at a specific time. Signal criticality defines the sum of the sensitivities of the control methods to an input signal, multiplied by the sum of the effectiveness of the control methods for a vehicle performance metric, multiplied by the importance of the real-time performance metrics.The VMC application further includes control logic for defining a vehicle performance metric for each actuator configuration for the vehicle such that the vehicle performance metric comprises one of the following: a no-effect contribution to achieving a VMC objective; a limited-effectiveness contribution to achieving the VMC objective; and a highly effective contribution to achieving the VMC objective. High effectiveness is greater than limited effectiveness, and limited effectiveness is greater than the no-effect contribution to the VMC objective. Each actuator configuration makes a specific and unique contribution to each performance metric, and each actuator configuration defines a particular subset of actuators with which the vehicle is equipped and contributes to the VMC in a different way.The VMC application also includes control logic for developing a VMC strategy based on the current VMC objectives and the effectiveness of the control methods with respect to the performance metrics and associated VMC objectives. The VMC strategy is based on the vehicle's real-time dynamic state, signal criticality, and signal reliability.The VMC application further includes control logic to use the VMC strategy to rank actuator control methods with respect to the current VMC objectives, to execute the VMC strategy based on the dynamic real-time vehicle condition, signal criticality, and signal reliability, and to actively, continuously, and automatically determine when a reliability of one or more input signals is equal to or below a predetermined reliability threshold for one or more input signals with a criticality equal to or above a predetermined criticality threshold.Upon determining that the reliability of the one or more input signals is equal to or below the predetermined reliability threshold and that the criticality of the one or more input signals is equal to or above the predetermined criticality threshold, active, continuous, and automatic adaptation is performed by using one or more alternative control methods with a reliability equal to or above the predetermined threshold for the criticality above the predetermined criticality threshold. If it is determined that the reliability of the one or more input signals is equal to or above the predetermined reliability threshold while the criticality is equal to or above the predetermined threshold, the highest-ranking control method applicable to the current VMC objectives is used.The VMC application further includes control logic that determines that the reliability of the one or more input signals is equal to or below the predetermined reliability threshold and that automatically transitions control of the actuator to one or more alternative actuator control methods that have less sensitivity to the one or more input signals identified as more reliable than the predetermined reliability threshold, compared to the highest-ranking control method applicable to the current VMC objectives. The automatic transition between the highest-ranking control method and one or more alternative actuator control methods is one or more of the following: automatic and instantaneous or automatic and stepwise.The VMC application also includes control logic for detecting and mitigating signal degradations by selectively applying one or more alternative VMC strategies; and for generating a VMC output command for the plurality of actuators based on the VMC strategy. The VMC strategy actively, continuously, and automatically adapts to seamlessly overcome the signal degradation by actively, continuously, and automatically executing a fusion degradation mitigation strategy that uses weighted averages of actuator control methods to define the VMC output command for the plurality of actuators. The VMC output command is calculated as follows: . Weighting index of a control method = [∑Sensitivity of a control method to input signal ×∑Reliability of input signal] × [∑Effectiveness of control method against performance metric ×∑Importance of a performance metric in real time] so that: Last actuator control command = Weighting index of a control procedure × Output of control procedure Weighting index of a control procedure wherein the weighting index for an actuator control method is calculated by multiplying the sensitivity of the control method by the reliability of the input signal and by the effectiveness of the actuator control method for a given actuator control algorithm and further multiplied by the importance of a real-time performance metric.

[0022] In another aspect of the present disclosure, the plurality of sensors includes one or more of the following: inertial measurement units (IMUs), suspension control units, semi-active damping suspension (SADS), GPS sensors, wheel speed sensors, throttle position sensors, accelerator pedal position sensors, brake pedal position sensors, steering position sensors, tire pressure monitoring sensors, and position sensors for aerodynamic elements. The plurality of actuators includes: in-plane actuators, including actuators for all-wheel drive (AWD), electronic all-wheel drive (eAWD), limited-slip differentials (LSDs), electronically controlled LSD (eLSD), active steering, or electronic power steering (EPS) on the front and / or rear axles of the vehicle. The plurality of actuators also includes out-of-plane actuators, including active aerodynamic actuators for one or more active aerodynamic elements, among others.: Spoilers, fans, intake devices, actively controlled venturi tunnels and manifolds; active suspension actuators including magnetorheological dampers and electrically, hydraulically or pneumatically adjustable dampers or springs.

[0023] Further areas of applicability will become apparent from the description provided herein. It should be understood that the description and specific examples are intended for purposes of illustration only and are not intended to limit the scope of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The drawings described herein are for illustrative purposes only and are not intended to limit the scope of the present disclosure in any way. Fig.1 is a schematic view of a system for improving vehicle motion control (VMC) performance using real-time data to assess reliability and criticality according to one aspect of the present disclosure; Fig. 2 is a flowchart illustrating the steps of the control logic of a VMC performance improvement application (VMC Application) of the VMC performance improvement system using real-time data reliability and criticality assessments of Fig. 1 according to one aspect of the present disclosure; and Fig. Figure 3 is a schematic representation of a portion of a vehicle that incorporates the VMC application of Fig. 1 for rollover avoidance according to one aspect of the present disclosure. DETAILED DESCRIPTION

[0025] The following description is merely illustrative in nature and is not intended to limit the present disclosure, its application, or uses.

[0026] Fig. 1 schematically shows a system 10 for improving the motion control (VMC) of a vehicle 12 using real-time data for reliability and criticality assessment. The system 10 operates in the vehicle 12. While the vehicle 12 shown is a passenger car, the vehicle 12 may also be a van, a bus, a semi-trailer truck, an SUV, a truck, a bicycle, an e-bike, a tricycle, a motorcycle, an airplane, a helicopter, an amphibious vehicle, or any other such vehicle without departing from the scope or purpose of the present disclosure. In the Fig.1, the vehicle 12 is equipped with a powertrain 14 capable of transmitting drive power to the wheels 16 of the vehicle and to the tires 18 attached to the wheels 16. The powertrain 14 may include a variety of components, such as internal combustion engines (ICEs) 20 and / or electric motors 22, and transmissions 24 capable of transmitting torque from the ICEs 20 and / or electric motors 22 to the wheels 16. In one example, the vehicle 12 may include an ICE 20 acting on the rear axle 26 of the vehicle 12 and one or more electric motors 22 acting on the front axle 28 of the vehicle 12.In further examples, the vehicle 12 may utilize one or more ICEs 20 and / or one or more electric motors 22 arranged in additional configurations that provide torque to either the front or rear axles 28, 26, or even individual wheels 16 of the vehicle 12, without departing from the scope or purpose of the present disclosure.

[0027] In several aspects, the powertrain 14 includes one or more co-located actuators 30. The co-located actuators 30 may include all-wheel drive (AWD) systems, including electronically controlled or electric AWD (eAWD) systems 32, and limited slip differentials (LSD) 34, including electronically controlled or electric LSD (eLSD) systems 36. Co-located actuators 30 may create or vary the force generation in the X and / or Y directions at the contact patch 38 between the tire 18 and the road surface within a predetermined capacity. An eAWD system 32 may transfer torque from the front to the rear of the vehicle 12 and / or from one side to the other of the vehicle 12. Likewise, an eLSD 36 may transfer torque from one side of the vehicle 12 to the other.In some examples, the eAWD 32 and / or the eLSD 36 may directly modify or control the torque output of the ICE 20 and / or the electric motors 22, and / or the eAWD 32 and the eLSD 36 may interact with a braking system 40 to adjust the amount of torque delivered to each tire 18 of the vehicle 12. Additional actuators 30 at the same level may include active steering or electronic power steering (EPS) systems 42 on the front and / or rear axles 28, 26. Active steering systems or EPS systems 42 may actively adjust an angle of the wheels 16 relative to the longitudinal axis X of the vehicle 12.

[0028] In further examples, the vehicle 12 may include a means for varying the normal force on each of the tires 18 of the vehicle 12 via one or more out-of-plane actuators 44. The out-of-plane actuators 44 of the vehicle 12 may include a plurality of actuators 44 that can control vertical movement of the vehicle 12. In several aspects, the out-of-plane actuators 44 may include active aerodynamic actuators 46, active suspension actuators 48, or the like. Active aerodynamic actuators 46 may actively or passively vary an aerodynamic profile of the vehicle via one or more active aerodynamic elements 49 such as wings, spoilers, fans or other intake devices, actively controlled venturis, splitters, or the like. Active suspension actuators 48 adjust suspension travel, spring rates, and damping characteristics.In some examples, the active suspension actuators 48 may include magnetorheological dampers, pneumatic dampers or springs, or other such electrically, hydraulically, or pneumatically adjusted dampers or springs without departing from the scope or purpose of the present disclosure.

[0029] The terms "front," "rear," "inside," "inward," "outside," "outward," "above," and "below" refer to the orientation of the vehicle 12 as illustrated in the drawings of this application. Thus, "forward" refers to a direction toward the front of a vehicle 12, "rearward" refers to a direction toward the rear of a vehicle 12, "left" refers to a direction toward the left side of the vehicle 12 relative to the front of the vehicle 12. Similarly, "right" refers to a direction toward the right side of the vehicle 12 relative to the front of the vehicle 12. "Inside" and "inward" refer to a direction toward the interior of a vehicle 12, and "outside" and "outward" refer to a direction toward the exterior of a vehicle 12, "below" refers to a direction toward the underside of the vehicle 12, and "above" refers to a direction toward the top of the vehicle 12.The terms "topmost," "overhanging," "bottom," "side," and "above" refer to the orientation of the actuators and vehicle 12 as generally illustrated in the drawings of this application. Although the orientation of the actuators 52 or vehicle 12 may vary depending on the application, these terms are intended to apply to the orientation of the components of system 10 and vehicle 12 as illustrated in the drawings.

[0030] The system 10 also includes one or more controllers 50. The controllers 50 are non-generalized electronic controllers having a pre-programmed digital computer or processor 52, a non-transitory computer-readable medium or memory 54 used to store data such as control logic, software applications, instructions, computer code, data, lookup tables, etc., and input / output (I / O) ports 56. Computer-readable media or memory 54 includes any type of media accessible by a computer, such as read-only memory (ROM), random access memory (RAM), hard disk drive, solid-state memory, compact disc (CD), digital video disc (DVD), or any other type of memory 54. Non-transitory computer-readable memory 54 excludes wired, wireless, optical, or other communication links that carry transitory electrical or other signals.Non-transitory computer-readable storage 54 includes media on which data can be permanently stored and media on which data can be stored and later overwritten, such as a rewritable optical disk or an erasable storage device. Computer code includes all types of program code, including source code, object code, and executable code. The processor 52 is configured to execute the code or instructions. The vehicle 12 may have controllers 50, including a dedicated Wi-Fi controller, an engine control module, a transmission control module, a body control module, a suspension control module, a brake control module, an infotainment control module, or the like. The I / O ports 56 may be configured to communicate via wired communication, wirelessly via IEEE 802.3af Wi-Fi protocols, or via a network.11x, cellular connections, satellite connections, or the like, without departing from the scope or purpose of this disclosure.

[0031] The on-board controller 50 also includes one or more applications 68. An application 68 is a software program configured to perform a particular function or group of functions. The application 68 may include one or more computer programs, software components, instruction sets, procedures, functions, objects, classes, instances, associated data, or a portion thereof suitable for implementation in suitable computer-readable program code. The applications 68 may be stored within the memory 54 or in additional or separate memory 54. In several aspects, the applications 68 may manage functions of the powertrain system, the suspension system, the braking system, the aerodynamic system, and / or the body system in an example vehicle 12.

[0032] The applications 68 that manage the functions of the powertrain system, the suspension system, the braking system, the aerodynamic system, and / or the body system in the vehicle 12 receive static and / or dynamic vehicle condition information or sensor data from a series of sensors 70 disposed on the vehicle 12. The sensors 70 may include a variety of sensors 70, including inertial measurement units (IMUs) 72, suspension control units such as semi-active damping suspension (SADS) 74, global positioning system (GPS) sensors 76, wheel speed sensors 78, throttle position sensors 80, accelerator pedal position sensors 82, brake pedal position sensors 84, steering position sensors 86, tire pressure monitoring sensors 88, aerodynamic element position sensors 90, and the like. IMUs 72 measure motion, acceleration and the like in multiple degrees of freedom.In a specific example, the IMUs 72 may measure position, motion, acceleration, and the like in three or more degrees of freedom. Likewise, the sensors of the SADS 74 may be IMUs 72 that can measure in three or more degrees of freedom. In some more specific examples, the SADS 74 may be an accelerometer for suspension or the like. The sensor data may therefore include, among other things: rotational speed data of the wheel 16, the SADS 74, and the IMU 72, including attitude, acceleration, and the like.

[0033] In several aspects, the sensor data from the sensors 70 is obtained via the I / O ports 56 by a VMC performance enhancement application (VMC application 92). The VMC application 92 uses the sensor data about the vehicle 12 to determine which positions the in-plane actuators 30 and the out-of-plane actuators 44 should assume to achieve a particular state of the vehicle 12 and to provide resilient, redundant, and accurate control of the movements of the vehicle 12.

[0034] The VMC application 92 receives sensor data from the one or more sensors 70 and the in-plane and out-of-plane actuators 30, 44 and transmits the sensor data as input signals to a series of subroutines of the VMC application 92, which process the sensor data to perform motion control functions of the vehicle 12, such as active downforce control, active steering, active suspension adjustments, dynamic roll and / or stability control, or the like. Because the VMC functions depend on the reliability of the input signals, the VMC functions may also be adversely affected if the reliability of the input signals decreases as the performance of the sensors 70 and the in-plane and out-of-plane actuators 30, 44 degrades over time.

[0035] Different control methods can achieve the same or similar VMC function results. For example, an active aerodynamic downforce control system may use multiple signals such as the acceleration of the vehicle 12 in the X and Y directions, the steering speed, and the engine torque as input signals. In classic control systems, if one such input signal, e.g., the acceleration in the X direction, becomes unreliable due to degradation or failure of the sensor 70, a classic active downforce control or control system may no longer properly and accurately control the VMC downforce functions. Similarly, a simplified classic control or control methodology may use fewer overall input signals to control the active downforce. In some examples, the simplified classic control method may use only the acceleration in the Y direction and the steering speed.However, when using the simplified classical control method, the VMC downforce functionality may not be able to be optimized situationally to achieve the best possible performance of the vehicle 12 because insufficient input data is available.

[0036] To avoid the ineffective results described above, the system 10 utilizes the VMC application 92 to combine and merge various control logic and input signals for the active control of various VMC functions to improve the performance and robustness of the motion control of the vehicle 12.

[0037] In Fig. 2, the system 10, in particular the VMC application 92, with further reference to Fig.1 is shown in more detail in diagram 200. The VMC application 92 receives sensor data from one or more sensors 70 and the in-plane and out-of-plane actuators 30, 44. The system 10 generates a plurality of measurements and estimates of the dynamic state of the vehicle 12 and wheel 16. Each dynamic state is represented in diagram 200 as a separate one of blocks 202, 204, 206, 208, and 210. The measurements and estimates of the dynamic state of the vehicle 12 and wheel 16 are used as inputs to the actuator control algorithm 212 of the VMC application 92. The actuator control algorithm 212 may include one or more actuator control sub-algorithms or subsystems AC1, AC2, AC3, etc., each managing different types of control. In several examples, AC1 defines an active aerodynamic control, such asan active downforce control, while AC2 defines an eLSD 36 control, and AC3 defines an active roll or sway control of the vehicle 12. Although only AC1, AC2, and AC3 are illustrated in the figures, any number of subalgorithms or subsystems may be used to control actuators without departing from the scope or purpose of the present disclosure. AC1, AC2, and AC3 each use one or more actuator control methods 214, 216, 218, 220, 222, 224 to control VMC performance. Each of the actuator control methods 214, 216, 218, 220, 222, 224 uses data obtained from a subset of the sensors 70 and the in-plane and out-of-plane actuators 30, 44 mounted on the vehicle 12 to determine a possible set of control commands for the in-plane and out-of-plane actuators 30, 44.

[0038] More specifically, a first actuator control method 214 of AC1 uses predefined and / or actively adjustable control or steering targets to assist in determining the in-plane and out-of-plane control outputs for the actuators 30, 44. In several examples, the first actuator control method 214 of AC1 includes steering target 1 and steering target 3, while the second actuator control method 216 of AC1 uses steering targets 1, 2, and 3, where steering target 1 is a lateral stability steering target, steering target 2 is a agility and handling steering target, and steering target 3 is a wheel stability steering target.It will be appreciated that, although only control objectives 1, 2, and 3 are illustrated and described herein, other control objectives may be part of any of the sub-algorithms or subsystems of the VMC performance enhancement system 10 of the vehicle 12 without departing from the scope or purpose of the present disclosure. In some other examples, the control objectives may include rollover prevention, wheel slip control such as traction and / or braking control, lateral stability, handling and maneuverability, or the like.

[0039] After receiving the measurements and estimates of the dynamic state of the vehicle 12 and the wheel 16, the actuator control algorithm 212 evaluates the reliability 226 and criticality 228 of the actuator control sub-algorithms or subsystems AC1, AC2, AC3, etc. The criticality 228 of input signals is determined based on signal sensitivity, actuator effectiveness, and the significance of a real-time performance metric 230. The sensitivity of an actuator control with respect to each signal is defined by how the control logic for the actuator depends on the corresponding signal. For example, a body control formulated based on an understeer angle is sensitive to the understeer estimate.However, if the control is designed based on yaw rate error, the body control logic is sensitive to yaw rate signals and desired yaw rate signals from the sensors 70 and the in-plane and out-of-plane actuators 30, 44 mounted on the vehicle 12. Actuator effectiveness is a measure of how effective the control logic for the respective actuators 30, 44 is with respect to a particular performance index. In one non-limiting example, an anti-roll stabilizer is used to control the roll motion of the vehicle 12. The significance of a real-time performance metric 230 is determined by the need for the performance metric 230 at a particular time.Stated another way, the criticality 228 of an input signal can be defined as the sum of the sensitivities of the control methods to the input signal, multiplied by the sum of the effectiveness of the control methods for a performance metric 230, multiplied by the real-time importance of a performance metric 230. The criticality 228 of the input signal provides the VMC application 92 with a real-time understanding of the performance metrics 230 while simultaneously considering the performance sensitivity of the actuator controller. Vehicle performance metrics 230 are defined for each actuator configuration for a particular vehicle 12 and a set of in-plane and out-of-plane actuators 30, 44 provided in the vehicle 12. Each actuator configuration has a specific contribution to each performance metric 230.An example of a comprehensive evaluation of the contributions of each actuator configuration to the performance metrics 230 is shown in the following table:. where for each contribution a “+” stands for a highly effective contribution, a “ / ” for a contribution with limited effectiveness and a “-” for no effect of the actuator configuration on a specific control objective.

[0040] The VMC application 92 then develops a VMC strategy based on the control objectives and the effectiveness of the control methods with respect to the performance metrics 230 and the associated objectives. It can be seen that certain in-plane and out-of-plane actuators 30, 44 can very effectively alter the motion of the vehicle 12 depending on certain circumstances or control objectives, as illustrated in the table above. Accordingly, the VMC application 92 determines which of the various available control commands are most effective at achieving the control objectives currently relevant to the VMC of the vehicle 12. That is, the VMC application 92 assigns a rank to each actuator controller AC1, AC2, AC3, etc. with respect to the control objective currently addressed by the VMC application 92. In the Fig.2, the aerodynamic control or active downforce of the vehicle 12 may be related to the handling and maneuverability and / or lateral stability of the vehicle 12. Torque vectoring (TV) and / or differential braking may be used to partially or fully achieve handling and maneuverability, lateral stability, rollover prevention, and wheel slip control. Likewise, active front-wheel steering and / or active rear-wheel steering may be used to partially or fully achieve the handling and maneuverability, lateral stability, and rollover prevention goals, while active anti-roll stabilizers may be used to partially achieve the handling and maneuverability, and rollover prevention goals.However, deviations from the above contributions to the various control objectives should be considered within the scope and purpose of the present disclosure.

[0041] In several aspects, the input signal criticality 228 and the input signal reliability are used to determine whether the reliability 226 is low for a given input signal with a high criticality rating 228. It should be noted that a high criticality rating 228 is greater than a low criticality rating 228, and that a high criticality rating 228 may be a criticality rating 228 that is equal to or greater than a predetermined criticality rating threshold 228. Likewise, it should be noted that a low reliability rating 226 is less than a high reliability rating 226, and that a low reliability rating 226 may be a reliability rating 226 that is equal to or less than a predetermined reliability rating threshold 226.More specifically, the system 10 and the VMC application 92 detect when performance degradation is occurring and actively, continuously, and automatically adapt to correct such degradation. Detecting performance degradation of a particular in-plane or out-of-plane actuator 30, 44 and / or sensor 70 is important because the quality of the signal data generated thereby can directly impact the accuracy of the control outputs to the various in-plane and / or out-of-plane actuators 30, 44 to effect VMC in a particular dynamic situation.Accordingly, if a signal from one or more of the sensors 70 and the in-plane and / or out-of-plane actuators 30, 44 is designated 232 as having low reliability 226, although it has high criticality 228, the VMC application 92 automatically switches to one or more of the other control methods 212, 214, etc., that utilize information from other sensors 70 or in-plane and / or out-of-plane actuators 30, 44.

[0042] More specifically, the VMC application 92 utilizes degradation mitigation logic to select control methods. As a non-limiting example, the control method selection logic may determine whether the reliability 226 of an input signal is below a threshold. Upon such a determination, the actuator controllers utilizing a control method that consumes the low-reliability signal 226 are switched to an alternative control method that is insensitive or has less sensitivity to the signals determined to be low-reliability signals 226.The degree of sensitivity of the control method to the low-reliability signal 226 is also important because if the sensitivity of the method is very low, the low-reliability signal 226 will have less impact on the reliability 226 and performance of the control method. The degradation mitigation logic of the VMC application 92 attempts to transition to an alternative control method before harmful VMC control actions can occur. The reliability 226 may fluctuate, but the VMC application 92 can switch between models gradually or instantaneously as needed. In further aspects, the reliability 226 of an actuator control subsystem decreases when the sensitivity to a low-reliability signal 226 is high.Accordingly, a failure mode of a particular actuator control subsystem may include operating regions where sensitivity to low-reliability signals 226 is high.

[0043] The VMC application 92 executes a degradation mitigation fusion strategy that uses weighted averages of the outputs of actuator control methods to define a final output command for the actuators of the vehicle 12. The fusion strategy is determined based on a number of criteria, including: reliability 226 and sensitivity of the input signals, as well as the effectiveness of a particular control method for the performance metrics 230 and the significance of each performance metric 230 in real time. A final actuator command may be calculated as follows: Weighting index of a control method = [∑Sensitivity of a control method to input signal ×∑Reliability of input signal] × [∑Effectiveness of control method against performance metric ×∑Importance of a performance metric in real time] so that: Last actuator control command = Weighting index of a control procedure × Output of control procedure Weighting index of a control procedure

[0044] Roughly speaking, the weighting index for an actuator control method is calculated by multiplying the relevant sensitivity by the reliability 226 and the effectiveness of a particular control algorithm, in turn multiplied by the importance of a performance metric 230. In some examples, to improve robustness, certain thresholds for minimum reliability and effectiveness indices 226 are set to decide whether control methods should be included in the fusion algorithm.

[0045] In Fig. 3 is further referred to Fig. 1 and Fig.2, an example of using the VMC application 92 to prevent rollovers is explained in more detail. Vehicle rollovers are a major safety issue for various vehicles 12. Various methods have been proposed to improve rollover stability, and the development of active rollover protection systems is still ongoing. The development of rollover prevention systems involves at least two steps: the detection of a rollover risk, and mitigation and control. Accordingly, precise knowledge of the rollover risk of a vehicle 12 is essential for the development of a practical rollover protection system. For the correct detection of rollovers, various rollover indices (Rls) are proposed, which define different formulations of rollover estimates. The Rls include: RI1 = LTR (load transfer ratio): ratio of lateral load transfer; RI2: based on the roll angle and lateral acceleration of the vehicle 12; RI3: based on the roll angle and roll rate of the vehicle 12; RI4: based on the height of the vehicle’s suspension 12; RI5: based on the deflection of the tire 18.

[0046] With regard to RI1 in particular, the LTR is the most reliable rollover index, which can be defined as follows: LTR=Fzr−FzlFzr+Fzl; where F zr and F zl the normal force for the right and left sides of the vehicle 12. One of the biggest challenges when using LTR is measuring or estimating the normal forces.

[0047] RI2, based on the roll angle of the vehicle 12 and the lateral acceleration, can be defined as follows: RI2=2msmT((hr+hscos φ)ayg+hssin φ) where m sthe sprung mass of the vehicle 12, m the total mass of the vehicle 12, h s the distance of the center of gravity of the vehicle 12 to the roll center of the vehicle 12, h R the roll center height of the vehicle 12, φ the roll angle of the vehicle 12, α y is the lateral acceleration of the vehicle 12, T is the track of the vehicle 12 and g is the acceleration due to gravity.

[0048] RI3, based on the roll angle and roll velocity of vehicle 12, can be defined as follows: RI3=−2(cφφ˙+kφφ)mgT where φ is the roll angle of the vehicle 12, φ̇ is the roll velocity of the vehicle 12, k φ the effective roll stiffness of the vehicle 12, c φ is the effective roll damping of the vehicle 12, m is the total mass of the vehicle 12, T is the track of the vehicle 12 and g is the acceleration due to gravity.

[0049] RI4, based on the suspension height of vehicle 12, addresses the differences between the suspension heights on the right and left sides, as these differences are indicators of the rollover risk of vehicle 12.

[0050] RI5, based on the deflection of tire 18 of vehicle 12, addresses the differences between the deflection of the right and left sides of tire 18, since the deflection on one side of vehicle 12, where tire 18 is more heavily loaded than on the other side of vehicle 12, is an indicator of rollover risk.

[0051] The VMC application 92 also determines the effectiveness of the various rollover prevention methods RI1, RI2, RI3, RI4, and RI5. The effectiveness of rollover prevention methods using a particular rollover index is determined by a confidence level for that index. This means that the indices that indicate rollover instability with a higher confidence level provide more effective rollover prevention control methods in a given situation. To merge three different stability indices, the criticality 228 of each index is considered. The criticality 228, or priority, of each index is defined as the extent to which the instability index is directly related to the instability of the body dynamics of the vehicle 12. Depending on the signals used and the type of method selected, the rollover indices may have different degrees of reliability 226.The reliability 226, or confidence level, of each index depends on the signals used and the relevant algorithms. The reliability 226 of the rollover indices is also included in the fusion process. Since the reliability 226 of different rollover indices can vary in real time, the VMC application 92 can assign different weights to the indices, knowing the vehicle type 12, the condition of the tires 18, the upcoming road geometry, etc.

[0052] In a first, non-limiting example, the system 10 employing the VMC application 92 uses three different control methods for active aerodynamic downforce control. Each of the control methods depends on different input signals and / or different combinations of input signals. Therefore, the reliability 226 of each of the three different control methods depends on the reliability 226 of the respective input signals. The first example method is generally based on longitudinal velocity (V-based), the second example method is based on steering angle and longitudinal velocity (Str-V-based), and the third example method is based on torque (or Fx), steering angle, and longitudinal velocity (Trq-Str-V-based).In general, in an idealized situation where all signals have the same reliability 226, Method 3 is considered the preferred solution for managing VMC via active aerodynamic downforce control, as the third method has the highest performance. However, since the reliability 226 of the Fx estimates is often low in practice, the first and / or second methods are used. Method 2 is good when Method 3 is not available, but if the steering and steering speed signals are not reliable enough, Method 1 should be used. Method 1 is simple but has the lowest performance compared to Methods 2 and 3. The sensitivity of each of the example control Methods 1, 2, and 3 to input signals is shown in the table below. Tax procedures Ay brake Vx Street Str-Rate Fx V-based M H H N N N Str-V-based L M H H M N Trq-Str-V-based L M H H M H where H = high sensitivity; M = medium sensitivity; and N = not sensitive.

[0053] In a second, non-limiting example, three different control methods for body control of the vehicle 12 using eAWD 32 to distribute torque to the front and rear axles 28, 26 are considered. Each control method depends on different input signals and / or different combinations of input signals, and the reliability 226 of each of the control methods is therefore dependent on the reliability 226 of the respective input signals. The first eAWD body control method utilizes the estimation of the lateral velocity of the vehicle 12 to calculate slip and ensure the stability of the vehicle body. The second method estimates road surface friction to calculate a desired yaw rate and yaw rate error to control the motion of the vehicle 12.The third method uses understeer angle estimates that are independent of longitudinal velocity (Vy) or road friction to control the movements of the vehicle 12.

[0054] In an idealized situation where all signals are reliable, the first method is the best solution because it has the highest performance when applied. However, since the reliability of the lateral velocity estimates may be low, the other two methods can be used. The second method is good when there is no method 1, but if the friction estimate is not reliable enough, the third method is necessary. The third method is independent of lateral velocity and road friction, but has the lowest performance compared to the other two methods.

[0055] In a somewhat more specific example of the second, non-limiting example, the reliability 226 of the Vy estimates is low, but the desired measurements or estimates of the yaw rate and understeer angle are reliable. Since the priority of the second control method is greater than that of the third control method, the second control method is used as long as the appropriate conditions exist. The reliability 226 of the friction estimate, and thus the reliability 226 of the desired yaw rates, may decrease in certain situations, but the understeer angle measurement may remain reliable. Using a transition strategy, the VMC application 92 of the body control may be performed through merged strategies based on both the second and third control methods, followed by a switch to control using the third method.In other situations, both the friction estimation and the lateral velocity estimation are unreliable, so that only the third control method comes into consideration.

[0056] A system and method for improving motion control of the vehicle 12 using real-time data to evaluate reliability 226 and criticality 228 of the present disclosure offers several advantages. These include providing a robust, redundant, and reliable means for achieving an optimal result in motion control of the vehicle 12 while simultaneously providing health monitoring and degradation mitigation for the multi-active, multi-criteria motion control of the vehicle 12, and while simultaneously providing a means for determining input signal criticality 228 and monitoring and generating performance metrics 230 for VMC subsystems in real time without increasing manufacturing complexity, while leveraging existing hardware and enhancing the customer experience.

[0057] The description of the present disclosure is merely exemplary, and variations that do not depart from the gist of the present disclosure are intended to be included within the scope of the present disclosure. Such variations are not to be regarded as a departure from the spirit and scope of the present disclosure.

Claims

[1] A system for improving the performance of vehicle motion control using real-time data to assess reliability and criticality, the system comprising: a vehicle; a plurality of sensors arranged on the vehicle that collect real-time information about a dynamic state of the vehicle; a plurality of actuators arranged on the vehicle that actively and continuously adjust the dynamic state of the vehicle; a controller having a processor, a memory, and one or more input / output (I / O) ports, the I / O ports communicating with the plurality of sensors and the plurality of actuators, the processor executing programmatic control logic stored in the memory, the programmatic control logic including a vehicle motion control (VMC) performance improvement application, the VMC application comprising: a first control logic for obtaining the real-time information about the dynamic state of the vehicle from the plurality of sensors and from the plurality of actuators; a second control logic for estimating a real-time dynamic vehicle state from the vehicle dynamic state information; a third control logic for determining a signal criticality and a signal reliability for information about the dynamic state of the vehicle; a fourth control logic for executing a VMC strategy based on the vehicle's real-time dynamic state, signal criticality, and signal reliability; a fifth control logic for detecting and mitigating signal degradation by selectively applying one or more alternative VMC strategies; and a sixth control logic for generating a VMC output command to the plurality of actuators based on the VMC strategy, wherein the VMC strategy actively, continuously, and automatically adapts to seamlessly overcome signal degradation. [2] The system of claim 1, wherein the second control logic further comprises: Measuring the position, motion, and acceleration of the vehicle in three or more degrees of freedom in real time with the plurality of sensors and the plurality of actuators, wherein each of the real-time dynamic state estimates defines a particular aspect of the dynamic state of the vehicle. [3] The system of claim 1, wherein the third control logic further comprises: Determining signal criticality based on signal sensitivity, actuator effectiveness of relevant actuators of the plurality of actuators, and the real-time importance of associated performance metrics, wherein signal sensitivity is a measure of how dependent the control logic for a particular actuator is on an associated control signal, wherein actuator effectiveness is a measure of the effectiveness of associated control logic controlling the particular actuators relative to a specific performance index, and wherein the real-time importance of associated performance metrics defines a necessity of the associated performance metric at a particular time; and where signal criticality defines the sum of the sensitivities of control methods to an input signal multiplied by the sum of the effectiveness of control methods for a vehicle performance metric multiplied by the importance of real-time performance metrics. [4] The system of claim 3, wherein for each actuator configuration for the vehicle, a vehicle performance metric is defined that includes one of the following features: a no-effect contribution to achieving a VMC target; a contribution of limited effectiveness to the achievement of the VMC objective; and a contribution of high effectiveness to the achievement of the VMC objective, where the high effectiveness is greater than the limited effectiveness and the limited effectiveness is greater than the contribution without effect to the achievement of the VMC objective; and where each actuator configuration makes a specific and unique contribution to each performance metric and each actuator configuration defines a unique subset of actuators with which the vehicle is equipped and contributes to the VMC in different ways. [5] The system of claim 4, wherein the VMC application executes the fourth control logic based on the real-time dynamic vehicle condition, signal criticality, and signal reliability and develops a VMC strategy related to the current VMC objectives and the efficiencies of control methods with respect to performance metrics and associated VMC objectives; and wherein the VMC strategy ranks the actuator control methods with respect to the current VMC objectives. [6] The system of claim 5, wherein the fifth control logic further comprises: Control logic that actively, continuously, and automatically determines when the reliability of one or more input signals is equal to or below a predetermined reliability threshold for one or more input signals with a criticality equal to or above a predetermined criticality threshold; and after determining that the reliability of the one or more input signals is equal to or below the predetermined reliability threshold and that the criticality of the one or more input signals is equal to or above the predetermined criticality threshold: actively, continuously, and automatically adjusting by using one or more alternative control methods with a reliability equal to or above the predetermined criticality threshold; and after determining that the reliability of the one or more input signals is equal to or above the predetermined reliability threshold while the criticality is equal to or above the predetermined threshold: using the control method applicable to the current VMC objectives with the highest rank in the ranking. [7] The system of claim 6, wherein the fifth control logic further comprises: Control logic that determines that the reliability of the one or more input signals is equal to or below the predetermined reliability threshold, and that automatically switches the actuator control to one or more alternative actuator control methods that have less sensitivity to the one or more input signals that have been identified as less reliable than the predetermined reliability threshold compared to the highest ranked control method for application to the current VMC objectives. [8] The system of claim 7, wherein the automatic switching between the highest priority control method and one or more alternative actuator control methods is automatic and instantaneous or automatic and stepwise. [9] The system of claim 7, wherein the sixth control logic further comprises: Control logic for actively, continuously, and automatically executing a fusion degradation mitigation strategy that uses weighted averages of actuator control methods to define the VMC output command to the plurality of actuators, wherein the VMC output command is calculated as follows: Weighting index of a control method = [∑Sensitivity of a control method to input signal ×∑Reliability of input signal] × [∑Effectiveness of control method against performance metric ×∑Importance of a performance metric in real time] so that: Last actuator control command = Weighting index of a control procedure × Output of control procedure Weighting index of a control procedure wherein the weighting index for an actuator control method is calculated by multiplying the sensitivity of the control method by the reliability of the input signal and by the effectiveness of the actuator control method for a given actuator control algorithm and further multiplied by the importance of a real-time performance metric. [10] A method for improving the performance of vehicle motion control using real-time data to assess reliability and criticality, the method comprising: Collecting real-time information about a dynamic state of the vehicle using a variety of sensors mounted on a vehicle; actively and continuously adjusting a dynamic state of the vehicle with a plurality of actuators arranged on the vehicle; Executing programmatic control logic including a vehicle motion control enhancement (VMC) application stored in a memory of a controller of the vehicle, the controller having a processor, a memory, and one or more input / output (I / O) ports, the I / O ports communicating with the plurality of sensors and the plurality of actuators, the VMC application including control logic comprising: Obtaining real-time information about the dynamic state of the vehicle from the plurality of sensors and from the plurality of actuators; Estimating a real-time dynamic vehicle state from the vehicle dynamic state information; Determining a signal criticality and a signal reliability for information about the dynamic state of the vehicle; Execute a VMC strategy based on the vehicle's real-time dynamic state, signal criticality, and signal reliability; Detecting and mitigating signal degradation by selectively applying one or more alternative VMC strategies; and Generating a VMC output command to the plurality of actuators based on the VMC strategy, wherein the VMC strategy actively, continuously, and automatically adapts to seamlessly overcome signal degradation.

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