Abstract: A vehicle, among other things, may use predicted rates of change in vehicle speed based on past driving data of a particular user to allocate resources within the vehicle, to recreate the behavior of particular user in an automated driving system, or to accurately predict a capability of the vehicle.

Abstract: A method of monitoring a fluid level in a power unit relies on a neural network model. The model is used to predict lateral acceleration during air ingestion events. These predictions are compared to measured values of lateral acceleration. When the measured values and the predicted values are not well correlated, a controller takes corrective action.

Abstract: A method for controlling a vehicle transmission system having a clutch system includes generating a torque-pressure (T-P) gain deviation based on a T-F characteristic and a nominal T-F characteristic for the clutch system, generating a pressure magnitude deviation based on the set of pressure values and the set of nominal pressure values, determining whether a T-F characteristic deviates from the nominal T-F characteristic based on the T-P gain deviation and the pressure magnitude deviation, identifying the T-F characteristic as deviating in response to the T-F characteristic departing from the nominal transfer characteristic, and issuing a notification regarding the deviating T-F characteristic to perform a corrective action related to the clutch system.

Abstract: A vehicle includes a powertrain, an inertial measurement unit configured to measure inertial forces exerted onto the vehicle, and a controller. The controller is programmed to control the torque at the powertrain based on a mapped relationship between the inertial forces and a vehicle velocity, wherein the mapped relationship utilizes at least one mapping parameter. The controller is further programmed to estimate a mass of the vehicle based on the mapping parameter.