A vehicle control system having a subsystem controller for initiating control of a first group of at least one vehicle subsystem in a selected one of a plurality of subsystem control modes each corresponding to one or more different driving conditions; and an estimator module for evaluating at least one driving condition indicator to determine the extent to which each of the subsystem control modes is appropriate and for providing an output indicative of the subsystem control mode that is most appropriate. The estimator module is configured to increase the probability to which the at least one off-road driving mode is determined appropriate in dependence on at least one terrain indicator. In an automatic response mode the subsystem controller selects the most appropriate one of the subsystem control modes for each subsystem of the first group in dependence on the output.

Automated launch torque is provided. An automated virtual launch torque generation (AVL-TG) system may be included in a vehicle, such as a heavy duty truck, that may interoperate with an adaptive cruise control (CC) system to move the vehicle from a standstill or low speed to a CC handover speed. The AVL-TG system may determine a tip-in torque curve configured to mimic a torque curve generated by a human operator's acceleration pedal tip-in from a standstill or low speed. The tip-in torque curve may be represented by torque demand values corresponding to a dynamic pedal saturation level applied over a dynamic pedal rate. The torque demand values determined by the AVL-TG system may mimic an expected or human vehicle operator generated torque request, and may operate to successfully close the clutch and smoothly launch the vehicle from a standstill or low speed.

A driving force control device for a vehicle is provided, which includes a motor, an engine, and a controller. The controller sets a target torque of the vehicle corresponding to accelerator operation, distributes a target engine torque, based on the target torque, and outputs a control signal corresponding to the target engine torque. The controller estimates a future amount of intake air to a cylinder based on the target engine torque, and estimates an engine torque after a setup time from the present time based on the estimated future amount of intake air. The controller sets a target motor torque after the setup time based on the estimated engine torque after the setup time so that the target torque is achieved, and outputs a control signal corresponding to the target motor torque to synchronize a torque response of the engine with a torque response of the motor.

A driving force control device for a vehicle is provided, which includes a motor, an engine, and a controller. The controller sets a target torque of the vehicle corresponding to accelerator operation, and distributes a target engine torque according to a distribution rule defined beforehand, based on the target torque of the vehicle, and outputs a control signal corresponding to the target engine torque to the engine. The controller estimates a future amount of intake air to a cylinder based on the target engine torque, and estimates a torque of the engine in the future based on the estimated future amount of intake air. The controller sets a target motor torque based on the estimated torque of the engine so that the target torque of the vehicle is achieved in the future, and outputs a control signal corresponding to the target motor torque to the motor.

A vehicle system is provided that optimizes vehicle operation by utilizing artificial intelligence and machine learning and providing dynamic changes to the vehicle characteristics. The vehicle system includes one or more sub-systems controlled by a vehicle operating system utilizing artificial intelligence and machine learning.

Systems and methods for operating a hybrid vehicle are presented. In one example, an integrated starter/generator (ISG) provides torque to restart an engine after the engine has been shut down and before engine speed is zero. An opening of a throttle is delayed to reduce driveline torque disturbances during engine restarting.

A method and system for blending between torque maps of a source propulsion of a vehicle. The method and system are particularly applicable to automatic selection of an alternative torque map in response to a change of vehicle operating condition, for example, a change of terrain. Blending may substantially avoid a step change in response of the source of propulsion as accelerator position is changed.

A vehicle system is provided that optimizes vehicle operation by utilizing artificial intelligence and machine learning and providing dynamic changes to the vehicle characteristics. The vehicle system includes one or more sub-systems controlled by a vehicle operating system utilizing artificial intelligence and machine learning.

A method and system for blending between torque maps of a source propulsion of a vehicle. The method and system are particularly applicable to automatic selection of an alternative torque map in response to a change of vehicle operating condition, for example, a change of terrain. Blending may substantially avoid a step change in response of the source of propulsion as accelerator position is changed.

A method and system is disclosed for blending between torque maps of a source of propulsion of a vehicle. Embodiments of the present invention are particularly applicable to automatic selection of an alternative torque map in response to a change of vehicle operating condition, for example a change of terrain. Blending according to embodiments of the present invention may substantially avoid a step change in response of the source of propulsion as accelerator position is changed.