A method for operating a hybrid vehicle includes obtaining propulsion switching data descriptive of a state of one or more vehicle systems for switching power flow of an internal combustion engine and an electric machine. The propulsion switching data may be used to provide a driver behavior recommendation and/or an actual environmental impact of the hybrid vehicle.

Methods and systems for improving fuel economy and reducing emissions of a vehicle with an electric motor, an engine, an energy storage device, and a controller are disclosed. The method includes obtaining current state information including a current hybrid control surface, and determining a target hybrid control surface for the vehicle based on the current state information.

Methods and systems for improving fuel economy and reducing emissions of a vehicle with an electric motor, an engine, an energy storage device, and a controller are disclosed. The method includes obtaining current state information including a current hybrid control surface, and determining a target hybrid control surface for the vehicle based on the current state information.

The operation of a hybrid powertrain system is optimized with respect to a desired state-of-charge trajectory, taking account of the estimated anticipated vehicle drive power. The hybrid powertrain system has an internal combustion engine and an electrically operated torque machine. The internal combustion engine and the torque machine are controlled by a control device and are connected to an output element via a hybrid transmission. Before the start of the prediction period Δt, an experience-based state-of-charge trajectory for the anticipated route, covering at least the prediction period Δt, is retrieved from an external database. The desired state-of-charge trajectory is established based on the experience-based state-of-charge trajectory by modifying it with at least one optimization constraint. The experience-based state-of-charge trajectory can be established based on operating data from hybrid powertrain systems of multiple vehicles and/or from operating data from multiple comparable journeys with the same vehicle.

The operation of a hybrid powertrain system is optimized with respect to a desired state-of-charge trajectory, taking account of the estimated anticipated vehicle drive power. The hybrid powertrain system has an internal combustion engine and an electrically operated torque machine. The internal combustion engine and the torque machine are controlled by a control device and are connected to an output element via a hybrid transmission. Before the start of the prediction period Δt, an experience-based state-of-charge trajectory for the anticipated route, covering at least the prediction period Δt, is retrieved from an external database. The desired state-of-charge trajectory is established based on the experience-based state-of-charge trajectory by modifying it with at least one optimization constraint. The experience-based state-of-charge trajectory can be established based on operating data from hybrid powertrain systems of multiple vehicles and/or from operating data from multiple comparable journeys with the same vehicle.

A controller for a hybrid electric vehicle including an internal combustion engine is provided. The internal combustion engine includes a filter arranged in an exhaust passage collect particulate matter from exhaust gas. The controller executes a first deceleration control process, a second deceleration control process, and a selection process. The first deceleration control process uses a fuel cutoff process when deceleration of the hybrid electric vehicle is required. The second deceleration control process does not use the fuel cutoff process when deceleration of the hybrid electric vehicle is required. The selection process selects execution of the second deceleration control process when a PM deposition amount is greater than or equal to a threshold value and selects execution of the first deceleration control process when the PM deposition amount is less than the threshold value.

Disclosed are a hybrid electric vehicle and an engine control method therefor that are capable of reducing entry of an engine into a full-load drive mode. The method includes determining whether the extent of depression of an accelerator pedal (APS) may be equal to or greater than a reference value set as a condition for entry of an engine into a full-load drive mode, determining a part-load torque corresponding to the maximum torque in a part-load drive mode of the engine and a motor torque corresponding to the maximum torque of a motor when the extent of depression of the accelerator pedal may be equal to or greater than the reference value, comparing the sum of the part-load torque and the motor torque with a driver demand torque, and controlling the engine in the full-load drive mode or the part-load drive mode depending on a result of the comparing.

A method includes receiving, by a remote server, operating parameters regarding one or more components of a vehicle from a vehicle controller of the vehicle; retrieving, by the remote server, at least one of static information or dynamic information regarding one or more parameters ahead of the vehicle; determining, by the remote server, an adjustment for at least one of the one or more components of the vehicle based on (i) the operating parameters and (ii) the at least one of the static information or the dynamic information; and providing, by the remote server, an instruction to the vehicle controller regarding the adjustment.

A controller for a hybrid electric vehicle including an internal combustion engine is provided. The internal combustion engine includes a filter arranged in an exhaust passage collect particulate matter from exhaust gas. The controller executes a first deceleration control process, a second deceleration control process, and a selection process. The first deceleration control process uses a fuel cutoff process when deceleration of the hybrid electric vehicle is required. The second deceleration control process does not use the fuel cutoff process when deceleration of the hybrid electric vehicle is required. The selection process selects execution of the second deceleration control process when a PM deposition amount is greater than or equal to a threshold value and selects execution of the first deceleration control process when the PM deposition amount is less than the threshold value.

Various embodiments include a driver assistance system for determining the position of a stopping point of a vehicle at an infrastructure device comprising: a control unit; a communication device for receiving data from a server or from the infrastructure device; and a sensor arrangement for capturing vehicle data or environmental data. The control unit determines the location of the stopping point at the infrastructure device based at least in part on the data and the vehicle data or environmental data.