Abstract: A fault remediation system for a vehicle includes one or more controllers in electronic communication with one or more consumed interfaces and one or more provided interfaces. The one or more controllers execute instructions to receive, from the one or more consumed interfaces, a consumed signal and perform fault detection upon the consumed signal to determine the presence of an active fault within the consumed signal. In response to detecting an active fault with the consumed signal, the one or more controllers select a remediation state from a group of two or more prospective remediation states based on a significance analysis of the consumed signal. The one or more controllers evaluate a relevant subfunction that corresponds to the consumed signal that the remediation state addresses for the presence of remediation tolerance and generates arbitration instructions based on the remediation tolerance.

Abstract: A driver command predictor includes a controller, multiple sensors, and a command prediction unit. The controller is configured to command an adjustment of multiple motion vectors of a vehicle relative to a roadway in response to multiple actual driver commands and multiple future driver commands. The actual driver commands are received at a current time. The future driver commands are received at multiple update times. The update times range from the current time to a future time. The sensors are configured to generate sensor data that determines multiple actual states of the vehicle in response to the motion vectors as commanded. The command prediction unit is configured to generate the future driver commands at the update times in response to a driver model. The driver model operates on the actual driver commands and the actual states to predict the future driver commands at the update times.

Abstract: A vehicle motion control system includes one or more input devices for generating one or more input signals associated with data indicative of a motion of the vehicle. The system further includes a computer, which has one or more processors. The computer further includes a non-transitory computer readable storage medium for storing instructions, such that the processor is programmed to compare a current tire state and a current tire prediction model to the data indicative of the motion of the vehicle. The processor is further programmed to calculate in real-time an adjusted tire state and an adjusted tire prediction model. The processor is further programmed to generate in real-time one or more actuation signals based on the adjusted tire state and the adjusted tire prediction model. The actuators in real-time adjust the motion of the vehicle in response to the actuator receiving the actuation signal from the processor.

Abstract: A method for vehicle motion control includes receiving sensor data from a plurality of sensors of a vehicle and monitoring a vehicle response of the vehicle using the sensor data. The vehicle response is represented by a plurality of vehicle-response signals. The method further includes fusing the plurality of vehicle-response signals to obtain at least one fused signal. The method further includes determining whether to activate a vehicle stability control of the vehicle based on the at least one fused signal and commanding the vehicle to activate the vehicle stability control in response to determining to activate the vehicle stability control of the vehicle based on the at least one fused signal.

Abstract: A system for supervisory control for eAWD and eLSD in a motor vehicle includes a control module, and sensors and actuators disposed on the motor vehicle. The sensors measure real-time motor vehicle data, and the actuators alter behavior of the motor vehicle. The control module receives the real-time data; receives one or more driver inputs to the motor vehicle; determines a status of a body of the motor vehicle; determines a status of axles of the motor vehicle; determines a status of each wheel of the motor vehicle; and generates a control signal to the actuators from the driver inputs and the body, axle, and wheel statuses. The control module also exercises supervisory control by actively adjusting constraints on the control signal to each of the actuators where actively adjusting constraints on the control signal alters boundaries of control actions in response to the one or more driver inputs.

Abstract: Systems and methods for vehicle motion control are provided. The method includes: calculating a correction factor using one of three different sets of operations when the vehicle is performing a limit handling maneuver, wherein the correction factor is calculated using a first set of operations when the vehicle is operating in an understeer state, calculated using a second set of operations when the vehicle is operating in an oversteer state, and calculated using a third set of operations when the vehicle is operating in a neutral steer state; adjusting a desired lateral acceleration and a desired yaw rate by applying the correction factor to account for a reduced level of friction experienced by the vehicle when traveling on a non-ideal friction surface; calculating optimal control actions based on the adjusted desired lateral acceleration and adjusted desired yaw rate; and applying the optimal control actions with vehicle actuators during vehicle operations.

Abstract: Systems and methods for controlling a vehicle are provided. The systems and methods include a sensor system and a processor configured to execute program instructions, to cause the at least one processor to: receive yaw rate values, lateral acceleration values and longitudinal velocity values for the vehicle from the sensor system, determine side slip angle parameter values based on the yaw rate values, lateral acceleration values and longitudinal velocity values, determine phase portrait angles based on the side slip angle parameter values and the yaw rate values, wherein the phase portrait angles each represent an angle between yaw rate and side slip angle for the vehicle in a phase portrait of yaw rate and side slip angle, detect or predict vehicle instability based at least on the phase portrait angles, and when vehicle instability is detected or predicted, control motion of the vehicle to at least partly correct the vehicle instability.

Abstract: A method of controlling a vehicle includes obtaining a linear representation of a vehicle dynamics model that includes actuator dynamics u integrated with vehicle dynamics x. The actuator dynamics u include a road wheel angle at rear wheels ?r and a torque Mz. The method also includes obtaining an objective function based on a function of the vehicle dynamics x and the actuator dynamics u and formulating a cost function to minimize the objective function. The actuator dynamics u including the torque Mz are determined for a next time sample based on minimizing the objective function. The vehicle is controlled to implement the torque Mz.

Abstract: A system for supervisory control for eAWD and eLSD in a motor vehicle includes a control module, and sensors and actuators disposed on the motor vehicle. The sensors measure real-time motor vehicle data, and the actuators alter behavior of the motor vehicle. The control module receives the real-time data; receives one or more driver inputs to the motor vehicle; determines a status of a body of the motor vehicle; determines a status of axles of the motor vehicle; determines a status of each wheel of the motor vehicle; and generates a control signal to the actuators from the driver inputs and the body, axle, and wheel statuses. The control module also exercises supervisory control by actively adjusting constraints on the control signal to each of the actuators where actively adjusting constraints on the control signal alters boundaries of control actions in response to the one or more driver inputs.

Abstract: A system for managing chassis and driveline actuators of a motor vehicle includes a control module executing program code portions that: cause sensors to obtain vehicle state information, receive a driver input and generate a desired dynamic output based on the driver input and the vehicle state information, and then estimate actuator actions based on the vehicle state information, generate one or more control action constraints based on the vehicle state information and estimated actuator actions, generate a reference control action based on the vehicle state information, the estimated actions of the one or more actuators and the control action constraints, and integrate the vehicle state information, the estimated actuator actions, desired dynamic output, reference control action and the control action constraints to generate an optimal control action that falls within a range of predefined actuator capacities and ensures driver control of the vehicle.

Abstract: Systems and methods for vehicle motion control are provided. The method includes: calculating a correction factor using one of three different sets of operations when the vehicle is performing a limit handling maneuver, wherein the correction factor is calculated using a first set of operations when the vehicle is operating in an understeer state, calculated using a second set of operations when the vehicle is operating in an oversteer state, and calculated using a third set of operations when the vehicle is operating in a neutral steer state; adjusting a desired lateral acceleration and a desired yaw rate by applying the correction factor to account for a reduced level of friction experienced by the vehicle when traveling on a non-ideal friction surface; calculating optimal control actions based on the adjusted desired lateral acceleration and adjusted desired yaw rate; and applying the optimal control actions with vehicle actuators during vehicle operations.

Abstract: Systems and methods for controlling a vehicle are provided. The systems and methods include a sensor system and a processor configured to execute program instructions, to cause the at least one processor to: receive yaw rate values, lateral acceleration values and longitudinal velocity values for the vehicle from the sensor system, determine side slip angle parameter values based on the yaw rate values, lateral acceleration values and longitudinal velocity values, determine phase portrait angles based on the side slip angle parameter values and the yaw rate values, wherein the phase portrait angles each represent an angle between yaw rate and side slip angle for the vehicle in a phase portrait of yaw rate and side slip angle, detect or predict vehicle instability based at least on the phase portrait angles, and when vehicle instability is detected or predicted, control motion of the vehicle to at least partly correct the vehicle instability.

Abstract: A driver command predictor includes a controller, multiple sensors, and a command prediction unit. The controller is configured to command an adjustment of multiple motion vectors of a vehicle relative to a roadway in response to multiple actual driver commands and multiple future driver commands. The actual driver commands are received at a current time. The future driver commands are received at multiple update times. The update times range from the current time to a future time. The sensors are configured to generate sensor data that determines multiple actual states of the vehicle in response to the motion vectors as commanded. The command prediction unit is configured to generate the future driver commands at the update times in response to a driver model. The driver model operates on the actual driver commands and the actual states to predict the future driver commands at the update times.

Abstract: A method of controlling a vehicle includes obtaining a linear representation of a vehicle dynamics model that includes actuator dynamics u integrated with vehicle dynamics x. The actuator dynamics u include a road wheel angle at rear wheels ?r and a torque Mz. The method also includes obtaining an objective function based on a function of the vehicle dynamics x and the actuator dynamics u and formulating a cost function to minimize the objective function. The actuator dynamics u including the torque Mz are determined for a next time sample based on minimizing the objective function. The vehicle is controlled to implement the torque Mz.

Abstract: A traction control module includes a sensor/estimation module configured to output wheel stability data based on a plurality of wheel condition inputs and a wheel stability monitoring module configured to calculate a plurality of wheel stability predictors based on the wheel stability data. Each of the wheel stability predictors is independently indicative of a wheel slip condition. The traction control module further includes a wheel stability data fusion module configured to receive each of the plurality of wheel stability predictors, combine selected wheel stability predictors from the plurality of wheel stability predictors to generate combinations of the wheel stability predictors, and selectively output a torque reduction request based on the combinations of the wheel stability predictors.

Abstract: Disclosed is an surface-coating robot operating system, a movable base (100) is provided to drive the whole operating system to implement autonomous navigation movement in the workspace; a vertical linear actuator (200) is used to drive a mechanical arm (300) to move up and down so as to meet the requirement for spraying at different heights; and the mechanical arm (300) is used to drive a spray gun (400) to implement multi-degree-of-freedom motion so as to meet the requirement for spraying at different positions; the whole spraying process is autonomously completed by the operating system, which is time-saving and labor-saving, high efficient, and ensures uniform spraying thickness, smooth spraying surface and consistent spraying quality; the robotic spraying may obviously reduce the coating dusts generated in a spraying process and the human risk caused by exposure to harmful coating chemicals. An operating method for surface-coating robot is disclosed.