Abstract: A method for use with a vehicle having one or more subsystems includes receiving vehicle health management (VHM) information via a controller indicative of a state of health of the subsystem. The VHM information is based on prior testing results of the subsystem. The method includes determining a required testing profile using the testing results, applying the testing profile to the subsystem to thereby control a state of the subsystem, and measuring a response of the subsystem to the applied testing profile. The method also includes recording additional testing results in memory of the controller that is indicative of a response of the subsystem to the applied testing profile. The vehicle includes a plurality of subsystems and a controller configured to execute the method.

Abstract: A method proactively transitions performance of a functional operation from a primary subsystem to a secondary subsystem within a vehicle or other system having an electronic control unit (ECU). The method includes receiving health management information via the ECU when the primary subsystem is actively performing the functional operation within the system and the secondary subsystem operates in a standby mode, wherein the health information is indicative of a numeric state of health (SOH) of the primary subsystem. The method also includes comparing the numeric SOH to a calibrated non-zero threshold SOH, and then commanding, via the ECU, a transition of the performance of the functional operation to the secondary subsystem and placing the primary subsystem in the standby mode when the numeric SOH is less than the calibrated non-zero threshold SOH. A vehicle executes the method via the ECU.

Abstract: A perception module of a spatial monitoring system to monitor and characterize a spatial environment proximal to an autonomous vehicle is described. A method for evaluating the perception module includes capturing and storing a plurality of frames of data associated with a driving scenario for the autonomous vehicle, and executing the perception module to determine an actual spatial environment for the driving scenario, wherein the actual spatial environment for the driving scenario is stored in the controller. The perception module is executed to determine an estimated spatial environment for the driving scenario based upon the stored frames of data associated with the driving scenario, and the estimated spatial environment is compared to the actual spatial environment for the driving scenario. A first performance index for the perception module is determined based upon the comparing, and a fault can be detected.

Abstract: A scheduling controller in communication with a plurality of autonomous vehicles is described, and includes an operator request compiler, a fleet state-of-health database, an environmental conditions compiler and a fleet scheduling controller. The fleet scheduling controller is configured to deploy the autonomous vehicles based upon inputs from the operator request compiler, the fleet state-of-health database and the environmental conditions compiler. A process for coordinating a fleet of autonomous vehicles includes determining states of health for the autonomous vehicles, and determining a desired autonomous vehicle use requirement from each of a plurality of operators that are associated with the autonomous vehicles. A usage schedule for each of the autonomous vehicles is determined based upon the states of health and the desired autonomous vehicle use requirements from the operators. The autonomous vehicles are deployed based upon the usage schedule.

Abstract: A controller architecture for monitoring an autonomic vehicle control system includes a first controller, a second controller, a telematics controller, a third controller, a plurality of subsystem controllers, a first and a second communication bus, and a first and a second communication link. The telematics controller in communication with the first controller. The second controller includes a second processor and a second memory device. Each subsystem controller is configured to effect operation of one of a subsystem, wherein each of the subsystem controllers includes a vehicle health monitor (VHM) agent. The third controller includes a third processor and a third memory device. A first instruction set includes a prognostic classification routine based upon inputs from the VHM agents of the plurality of subsystem controllers. The telematics controller is disposed to communicate an output from the prognostic classification routine to an off-board controller.

Abstract: A method and associated device for automated maintenance scheduling for an autonomous vehicle includes monitoring a state of health (SOH) of an on-vehicle subsystem and monitoring an appointment log associated with a vehicle operator. Upon detecting a change in the SOH of the on-vehicle subsystem, the method includes communicating with a service center to determine a recommended maintenance action associated with the change in the SOH of the on-vehicle subsystem and to determine a proposed service appointment for the autonomous vehicle to effect the recommended maintenance action. The proposed service appointment is coordinated with the appointment log, and verified with the vehicle operator. A service appointment is scheduled based upon the proposed service appointment when verified by the vehicle operator. The appointment log is updated to include the service appointment.

Abstract: A method of conducting prognosis for an airflow management system for a combustion engine includes adjusting a throttle body valve position control signal in response to a detected airflow variation and monitoring an airflow variation compensation (AVC) value corresponding to a degree of adjustment of the control signal. The method also includes generating a throttle body coking severity metric based on at least a plurality of residual error values and the AVC value, and executing at least one response action based on the throttle body coking severity metric exceeding a predetermined threshold.

Abstract: A method of predicting the health of and controlling a hydraulic pressure actuated torque converter lock-up clutch includes determining rotational input and output speeds of the torque converter. The method also includes determining a magnitude of the hydraulic pressure. The method additionally includes determining a level of performance of the clutch across multiple torque converter operating modes using the determined input and output torque converter speeds and the determined magnitude of the hydraulic pressure. The method also includes calculating a numeric state of health (SOH) coefficient of the clutch that quantifies a relative severity of degradation of a plurality of clutch characteristics across the multiple torque converter operating modes. Furthermore, the method includes executing a control action relative to the clutch when the calculated numeric SOH coefficient for specified torque converter operating mode(s) is less than a calibrated SOH threshold.

Abstract: An engine coolant system includes a variable-opening valve having a plurality of tubes in fluid flow communication with an engine block and a radiator. The coolant system also includes an electrically-powered pump arranged to cycle coolant through the radiator and the engine block to regulate an engine temperature. The coolant system further includes a controller programmed to store a baseline relationship between pump speed and pump power draw using a nonlinear scale. The controller is also programmed to detect a steady state operating condition of the pump, and identify an operational relationship between real-time pump speed and a pump power draw. The controller is further programmed to detect a coolant leak based on a deviation between the baseline relationship and the operational relationship.

Abstract: A thermal management system includes an electric coolant pump, power source, and controller. The pump is in fluid communication with a heat source and a radiator, and has pump sensors for determining a pump voltage, speed, and current. The battery energizes the sensors. The controller receives the voltage, speed, and current from the sensors, determines a performance of the pump across multiple operating regions, calculates a numeric state of health (SOH) quantifying degradation severity for each of a plurality of pump characteristics across the regions, and executes a control action when the calculated numeric SOH for any region is less than a calibrated SOH threshold. The pump characteristics include pump circuit, leaking/clogging, bearing, and motor statuses. A vehicle includes an engine or other heat source, a radiator; and the thermal management system. The controller may execute a prognostic method for the electric coolant pump in the vehicle.

Abstract: An engine airflow management system includes an inlet portion to receive ambient air and a mass airflow (MAF) sensor to sense mass flow rate of air passed through the inlet portion. The airflow management system includes a throttle body to selectively restrict airflow and a throttle position sensor (TPS) to sense an opening value of the throttle body. The airflow management system includes an intake manifold in fluid connection with the throttle body configured to direct airflow to a number of combustion cylinders. A manifold air pressure (MAP) sensor detects air pressure at the intake manifold. A controller is programmed to monitor signals from each of the MAF sensor, TPS, and the MAP sensor and generate a residual error value based on a difference between a model-based value and a corresponding monitored signal. A response action is based on a trend of at least two residual error values.

Abstract: An engine coolant system includes a variable-opening valve having a plurality of tubes in fluid flow communication with an engine block and a radiator. The coolant system also includes an electrically-powered pump arranged to cycle coolant through the radiator and the engine block to regulate an engine temperature. The coolant system further includes a controller programmed to store a baseline relationship between pump speed and pump power draw using a nonlinear scale. The controller is also programmed to detect a steady state operating condition of the pump, and identify an operational relationship between real-time pump speed and a pump power draw. The controller is further programmed to detect a coolant leak based on a deviation between the baseline relationship and the operational relationship.