Abstract:
A first network device includes a transceiver, a memory and a control module. The transceiver receives an integrated model from a second network device that is separate from the first network device. The memory stores the integrated model and diagnostic trouble code data, most probable cause data, and least probable cause data, which have corresponding cause of issue indications for an issue of a vehicle. The control module while executing the integrated model: compares the cause of issue indications to determine whether the cause of issue indications are consistent such that a same cause of issue is indicated; in response to the cause of issue indications being consistent, displays the same cause of issue, and in response to the cause of issue indications being inconsistent and based on a set of conditions, displays a portion of health related information while refraining from displaying another portion of the health related information.
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 controller area network (CAN) includes a CAN bus having a CAN-H wire, a CAN-L wire, and a pair of CAN bus terminators located at opposite ends of the CAN bus. The CAN further includes a plurality of nodes including controllers wherein at least one of the controllers is a monitoring controller. The monitoring controller includes a CAN monitoring routine for detecting a wire short fault in the CAN bus and its location.
Abstract:
A controller area network (CAN) has a plurality of CAN elements including a communication bus and a plurality of controllers. A method for monitoring the CAN includes detecting occurrences of a first short-lived fault and a second short-lived fault within a predefined time window. A first fault set including at least one inactive controller associated with the first short-lived fault and a second fault set including at least one inactive controller associated with the second short-lived fault are identified. An intermittent fault is located in the CAN based upon the first and second fault sets.
Abstract:
An embodiment contemplates a method of determining a state-of-charge of a battery for a vehicle. (a) An OCV is measured for a current vehicle ignition startup after ignition off for at least eight hours. (b) An SOCOCV is determined for the current vehicle ignition startup. (c) An SOCOCV—est is is determined for a current vehicle ignition startup. (d) A determination is made whether the difference in the SOCOCV for the current startup and the SOCOCVest for the current startup is less than a predefined error bound using. Steps (a)-(d) is performed in response to the difference being greater than the predefined error; otherwise, determining an ignition-off current for the current vehicle ignition startup as a function of the SOCOCV of the current vehicle ignition startup and previous vehicle ignition startup, and a SOC based on current integration over time. Determining an SOCest of the current vehicle ignition startup using the processor.
Abstract:
A vehicle includes a system and method of operating the vehicle. The system includes a camera, a map database and a processor. The camera obtains camera data of a location of a road being traversed by the vehicle. The map database provides map data of the location of the road. The processor determines a first curvature of the road at the location from the camera data, determines a second curvature of the road at the location from the map data, identifies a mismatch between the first curvature and the second curvature at the location of the road, generates a case report for one of the map data and the camera data at the location upon occurrence of the mismatch, and adjusts one of the map data and a confidence level in the camera data for the location based on the case report.
Abstract:
An autonomous driving system for an autonomous vehicle includes a plurality of on-board autonomous sensors that sense data related to operation of the autonomous vehicle and a surrounding environment and an automated driving controller in electronic communication with the plurality of on-board autonomous sensors. The automated driving controller is instructed to receive an indication one or more of the plurality of on-board autonomous sensors are non-functional and a secondary autonomous sensor system including one or more replacement sensors are installed. The automated driving controller is instructed to verify the secondary autonomous sensor system based on a security check and perform a redundancy check between the one or more replacement sensors and the plurality of on-board autonomous sensors. In response to determining the one or more replacement sensors are valid based on the redundancy check, the automated driving controller operates the autonomous vehicle in a limp home mode.
Abstract:
A system for a vehicle includes a plurality of sensors onboard the vehicle and a controller. A first sensor of the plurality of sensors is configured to detect lane markings on a roadway. The controller is configured to store data from the plurality of sensors. In response to receiving an indication indicating a misdetection of lane markings on the roadway based on data received from the first sensor, the controller is configured to execute in parallel a plurality of procedures configured to detect a plurality of causes for the misdetection of lane markings, respectively, based on the stored data; isolate one of the causes as a root cause for the misdetection of lane markings; and provide a response for mitigating the misdetection of lane markings on the roadway based on the root cause for the misdetection of lane markings.
Abstract:
An autonomous driving system for an autonomous vehicle includes an automated driving controller wirelessly connected to a towing taxi. The automated driving controller determines the autonomous driving system is non-functional. In response to determining the autonomous driving system is non-functional, the automated driving controller generates a notification indicating the autonomous driving system is non-functional. The automated driving controller receives, from the towing taxi, a current data string including a data point corresponding to a current point in time in combination with a predicted data point for each of one or more predicted points of time in the future. The current data string is compared with a previous data string recorded at a previous point in time. In response to determining the current data string matches the previous data string, the automated driving controller determines one or more driving maneuvers for the autonomous vehicle based on the current data string.