Gm Global Technolgoy Operations, Inc.

Joshua J Sanchez

Xinyu Du

Paul Edward Krajewski

Yilu Zhang

Varsha K Sadekar

Shengbing Jiang

Yao Hu

Steven W Holland

Atul Nagose

Mateusz M Nowak

Zhongyu Yang

Kevin M Corr

Eric J Baur

A system includes an assessment module and a training module. The assessment module is configured to receive event data about an event associated with a subsystem of a vehicle. The assessment module is configured to determine deviations between reference data for the subsystem indicating normal operation of the subsystem and portions of the event data that precede and follow the event. The assessment module is configured to determine whether the event data indicates a fault associated with the subsystem by comparing the deviations to a threshold deviation. The training module is configured to update a model trained to identify faults in vehicles to identify the event as a fault associated with the subsystem of the vehicle based on the event data in response to the deviations indicating a fault associated with the subsystem.

Adaptive prognostics systems and methods for vehicles

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.

Selective health information reporting systems including integrated diagnostic models providing least and most possible cause information

A controller processes data from one or more sensors of a subsystem of a vehicle. The processing includes smoothing the data and calculating a mean of the data. The controller identifies a transition point in the processed data where a moving average of the data is less than the mean by a predetermined amount indicating a trend. The controller selects a segment of the processed data subsequent to the transition point, detects the trend in the segment using regression, and extrapolates the detected trend to reach a predetermined fault threshold. The controller predicts a failure of the subsystem based on a slope of the extrapolated trend and provides an indication of the prediction based on the slope to schedule a service for the subsystem.

Vehicle fault diagnostics and prognostics using automatic data segmentation and trending

A method and system of diagnosing and suggesting least probable faults for an exhibited vehicle failure. The method includes initiating a vehicle health management (VHM) algorithm to monitor a state of health (SOH) for at least one vehicle component at each vehicle operating event over a predetermined time period. The VHM algorithm determines at least one of a Green SOH, a Yellow SOH, and a Red SOH designation with a confidence level for the at least one vehicle component; calculating a number of Green SOH designations (N) over the predetermined time period; and upon an exhibited vehicle failure, providing a least probable cause indication for the at least one component when a set of conditions are met. The set of conditions includes (i) Nis equal to or greater than a predetermined number of Green SOH designations and (ii) no Yellow SOH and Red SOH designations are present.

Method of enhanced component failure diagnosis for suggesting least probable fault

A method of diagnosing a root cause for an exhibited vehicle failure, comprises initiating a vehicle health management (VHM) algorithm, repeatedly monitoring, at a specified time interval, the state of health (SOH) for at least one vehicle component, wherein the SOH for the at least one vehicle component is one of Green (normal operation), Yellow, and Red, calculating a number of consecutive Green SOH results for the at least one vehicle component, and providing an indication of likelihood that the at least one vehicle component is not a root cause of the exhibited vehicle failure based on the number of consecutive Green SOH results for the at least one vehicle component.

Enhanced system failure diagnosis

A method for mitigating an electrical actuator fault in a system containing multiple actuators includes: applying multiple predetermined conditions to each of multiple actuators in a vehicle system to identify when at least one of the multiple actuators is in a faulted condition; and increasing an input voltage to all of the actuators to increase an output of the at least one of the multiple actuators in the faulted condition to mitigate the faulted condition.

Growing community of inventors

Sterling Heights, MI, United States of America

Joshua J Sanchez