Aspects of the present invention relate to a method and to a control system for controlling movement of a vehicle to provide vehicle creep, the vehicle comprising an engine and an electric traction motor, the control system comprising one or more controllers, wherein the control system is configured to: while a torque path between the engine and a first set of vehicle wheels is disconnected, control the electric traction motor to provide tractive torque to a second set of vehicle wheels to automatically move the vehicle to provide electric vehicle creep, wherein the electric vehicle creep is controlled by a mathematical model of engine creep torque that would be provided by the engine when the torque path between the engine and the first set of vehicle wheels is connected.

An active vibration reduction control apparatus for a hybrid electric vehicle includes: a reference signal generator generating a reference signal and a first phase based on a first rotational angle of a first motor; a vibration extractor extracting a vibration signal from a second motor; a coefficient determiner determining a filter coefficient which minimizes a phase difference between the reference signal and the vibration signal; a phase determiner detecting a second phase which corresponds to the phase difference using a first speed signal of the first motor and the filter coefficient; a phase deviation amount detector detecting a third phase for compensating for a phase delay; and a synchronization signal generator generating an antiphase signal of a shape of an actual vibration in order to determine a compensating force of the first motor.

The disclosure relates to a method for generating a reference trajectory within a lane for a vehicle. The method comprises receiving at least one vehicle current state parameter describing a current state of the vehicle (S11). The current state of the vehicle comprises at least a current position of the vehicle. Furthermore, a destination parameter describing a destination to be reached by the vehicle (S12), and at least one route parameter describing a route for reaching the destination (S13) are received. Moreover, the method comprises estimating a power loss being caused when traveling from the current position of the vehicle to the destination (S14). The reference trajectory within the lane is determined such that it minimizes the power loss and leads to the destination (S15). Additionally, a method for operating a vehicle is presented. According to this method, a reference trajectory is generated in accordance with the above method (S21) and at least one control signal is provided for controlling a motion of the vehicle along the reference trajectory (S22). Furthermore, a data processing apparatus, a vehicle and a computer-readable medium are presented.

It is determined whether fuel efficiency of a vehicle is improved by operating a first rotating machine to generate electricity to such an extent that an electrical path amount becomes a desired electrical path amount for controlling an operating point of an engine to a desired operating point and driving and operating a second rotating machine as a second power source, the electrical path amount being a magnitude of electric power in an electrical path through which the electric power is transferred between the first rotating machine and the second rotating machine. When the electronic control device determines that the fuel efficiency of the vehicle is improved, the first rotating machine is operated to generate electricity to such an extent that the electrical path amount becomes the desired electrical path amount and the second rotating machine is driven and operated as the second power source.

A hybrid vehicle comprises an engine, an energy storage device, and an aftertreatment system comprising a SCR catalyst configured to treat constituents of an exhaust gas. A controller is operatively coupled to the engine, the energy storage device, and the after treatment system, and configured to estimate an exhaust gas temperature and flow rate of the exhaust gas based on a set of engine operating parameters. The controller determines an exhaust gas cooling rate based on the exhaust gas temperature, flow rate, and a SCR catalyst temperature, and an ambient cooling rate based on an ambient temperature, a vehicle speed and the catalyst temperature. The controller determines a SCR catalyst temperature change rate based on the exhaust gas and ambient cooling rates, and adjusts a load distribution between the engine and the energy storage device based on the SCR catalyst temperature change rate.

Methods and systems for a powertrain power management in a vehicle with an electric motor, and an engine are disclosed. The methods and systems involve a powertrain that is operatively coupled to the engine and the electric motor, and an optimizer module operatively coupled to the powertrain. The optimizer module receives an operator information to travel a route from a remote management module, receives current route information for the route from a mapping application in response to the operator information, measures current vehicle status information for the hybrid vehicle, and decides a power management strategy for the vehicle based on the current route information and the current vehicle status information.

A processor unit (3) is configured for executing an MPC algorithm (13) for model predictive control of a motor vehicle (1). The MPC algorithm (13) includes a longitudinal dynamic model (14) of the motor vehicle (1) and a cost function (15) to be minimized. The cost function (15) includes multiple terms, a first term of which represents an output of the cooling pump (28). In addition, the processor unit (3) is configured for, by executing the MPC algorithm (13) as a function of the longitudinal dynamic model (14), ascertaining a speed trajectory of the motor vehicle (1) situated within a prediction horizon and simultaneously ascertaining a pump operating value trajectory situated within the prediction horizon such that the first term of the cost function (15) is minimized.

A control system for a hybrid vehicle which includes an internal combustion engine and an electric motor and whose drive mode is switchable between an electric vehicle mode and a hybrid vehicle mode includes: an on-board learning unit mounted on the hybrid vehicle and configured to perform a learning action; a position determination unit configured to determine whether the hybrid vehicle is located in a low emission area where operation of the internal combustion engine is supposed to be restricted; and a learning control unit configured to at least partially stop the learning action of the on-board learning unit when determination is made that the hybrid vehicle is located in the low emission area.

Engine systems, vehicles and methods related to refueling in conjunction with infrastructure to vehicle communication. A vehicle or engine system may receive refueling information including a fuel quantity at a refueling event, and uses the refueling information to identify and/or eliminate measurement or modelling bias in the underlying engine system controls. The vehicle may also self-determine fuel efficiency. The vehicle may use charging data, rather than refueling data, to perform calculations of battery life, state of charge, state of health, and efficiency in electric vehicle examples.

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.