A hybrid vehicle includes an electric motor, a power storage device, an engine, and a controller. The controller executes switching control for switching control modes. The controller adds, to a first traveling distance, a traveling distance that is obtained when a state in which the engine is not operating and a power storage amount of the power storage device is higher than a threshold continues, and adds, to a second traveling distance, a traveling distance that is obtained when a state in which the engine is not operating and a charge depleting mode is selected continues.

A hybrid vehicle includes an electric motor, a power storage device, an engine, and a controller. The controller executes switching control for switching control modes. The controller adds, to a first traveling distance, a traveling distance that is obtained when a state in which the engine is not operating and a power storage amount of the power storage device is higher than a threshold continues, and adds, to a second traveling distance, a traveling distance that is obtained when a state in which the engine is not operating and a charge depleting mode is selected continues.

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 system includes a battery, an engine, and a processor. The processor is configured to plan, according to a model, an activation action of the engine of a vehicle for a next road segment subsequent to a current road segment; and activate, for the next road segment, the engine according to the activation action. The model includes a state space that includes a navigation map, which includes the current road segment of the vehicle, a current charge level of the battery, and whether the engine is currently on or off. The activation action is selected from a set comprising a first action to turn on the engine to charge the battery and a second action to turn off the engine.

A vehicle with a hybrid drivetrain including a fuel-fed engine coupled to a first drive axle, an electric motor coupled to a second drive axle and an APU for providing electrical power at stopover locations, and further including a controller for determining a location of the vehicle, a location of a stopover location, determining a target SOC of a battery for operating the APU at the stopover location and operating a hybrid control system to provide the target SOC for the vehicle at the stopover location.

A communication device acquires schedule information in which a schedule of a user who uses a hybrid electric vehicle is recorded. The schedule information includes a traveling schedule for causing the hybrid electric vehicle to travel in a predetermined period. The predetermined period is a period from when fuel of an engine is refueled to a predetermined deterioration time. When a traveling distance in a long-distance traveling schedule is a first distance, an ECU increases a usage ratio of the engine in the predetermined period than when the traveling distance is a second distance that is longer than the first distance. The long-distance traveling schedule is a schedule included in the traveling schedule and in which the hybrid electric vehicle travels for a predetermined distance or longer.

A communication device acquires schedule information in which a schedule of a user who uses a hybrid electric vehicle is recorded. The schedule information includes a traveling schedule for causing the hybrid electric vehicle to travel in a predetermined period. The predetermined period is a period from when fuel of an engine is refueled to a predetermined deterioration time. When a traveling distance in a long-distance traveling schedule is a first distance, an ECU increases a usage ratio of the engine in the predetermined period than when the traveling distance is a second distance that is longer than the first distance. The long-distance traveling schedule is a schedule included in the traveling schedule and in which the hybrid electric vehicle travels for a predetermined distance or longer.

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.

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.