Abstract: A powertrain control system for a plugin hybrid electric vehicle. The system comprises an adaptive charge sustaining controller; at least one internal data source connected to the adaptive charge sustaining controller; and a memory connected to the adaptive charge sustaining controller for storing data generated by the at least one internal data source. The adaptive charge sustaining controller is operable to select an operating mode of the vehicle's powertrain along a given route based on programming generated from data stored in the memory associated with that route. Further described is a method of adaptively controlling operation of a plugin hybrid electric vehicle powertrain comprising identifying a route being traveled, activating stored adaptive charge sustaining mode programming for the identified route and controlling operation of the powertrain along the identified route by selecting from a plurality of operational modes based on the stored adaptive charge sustaining mode programming.

Abstract: The technology described herein provides a powertrain system with a route-learning feature. Particularly, learned information is used to optimize powertrain operation along any learned route. The learned information comprises, generally, feedback from the vehicle's acceleration and brake sensors and information from an on-board trip computer. At the least, the powertrain is able to optimize its operation to a driver's preference based on the feedback recorded along a particular route that the driver has specified. The route-learning powertrain control described herein is particularly useful with a hybrid powertrain, and can be used to optimize start/stop and regenerative braking control. The system described herein can also be integrated with a navigation system and GPS receiver, to provide more accurate route-learning and/or automated operation.

Abstract: A powertrain control system for a plugin hybrid electric vehicle. The system comprises an adaptive charge sustaining controller; at least one internal data source connected to the adaptive charge sustaining controller; and a memory connected to the adaptive charge sustaining controller for storing data generated by the at least one internal data source. The adaptive charge sustaining controller is operable to select an operating mode of the vehicle's powertrain along a given route based on programming generated from data stored in the memory associated with that route. Further described is a method of adaptively controlling operation of a plugin hybrid electric vehicle powertrain comprising identifying a route being traveled, activating stored adaptive charge sustaining mode programming for the identified route and controlling operation of the powertrain along the identified route by selecting from a plurality of operational modes based on the stored adaptive charge sustaining mode programming.

Abstract: The technology described herein provides a powertrain system with a route-learning feature. Particularly, learned information is used to optimize powertrain operation along any learned route. The learned information comprises, generally, feedback from the vehicle's acceleration and brake sensors and information from an on-board trip computer. At the least, the powertrain is able to optimize its operation to a driver's preference based on the feedback recorded along a particular route that the driver has specified. The route-learning powertrain control described herein is particularly useful with a hybrid powertrain, and can be used to optimize start/stop and regenerative braking control. The system described herein can also be integrated with a navigation system and GPS receiver, to provide more accurate route-learning and/or automated operation.