An electric power steering device 100 includes: an electric motor 110 configured to apply a driving force to steer a wheel in response to operation of a steering wheel; and a control device 10 configured to perform control of drive of the electric motor by estimating a degree of sloping in a transverse direction of a roadway on which a vehicle travels, determining, based on the estimated degree of sloping, a correction current for correcting a target current required for the electric motor to generate the driving force, and correcting the target current with the correction current.

An electric power steering device 100 includes: an electric motor 110 configured to apply a driving force to steer a wheel in response to operation of a steering wheel; and a control device 10 configured to perform control of drive of the electric motor by estimating a degree of sloping in a transverse direction of a roadway on which a vehicle travels, determining, based on the estimated degree of sloping, a correction current for correcting a target current required for the electric motor to generate the driving force, and correcting the target current with the correction current.

A method for estimating energy consumption of a vehicle includes receiving, from a remotely located computing device, standardized energy consumption data corresponding to at least one other vehicle, the standardized energy consumption data corresponding to energy consumption of the at least one other vehicle as a function of speed. The method further includes generating a scaling factor by comparing the energy consumption data corresponding to the energy consumption of the vehicle as a function of speed with the standardized energy consumption data. The method further includes scaling the standardized energy consumption data to generate a profile of the energy consumption efficiency of the vehicle. The method further includes generating a signal to selectively adjust at least one of a speed of the vehicle, at least one route characteristic of a portion of a route being traversed by the vehicle, and a torque demand of the vehicle.

A method for estimating energy consumption of a vehicle includes receiving, from a remotely located computing device, standardized energy consumption data corresponding to at least one other vehicle, the standardized energy consumption data corresponding to energy consumption of the at least one other vehicle as a function of speed. The method further includes generating a scaling factor by comparing the energy consumption data corresponding to the energy consumption of the vehicle as a function of speed with the standardized energy consumption data. The method further includes scaling the standardized energy consumption data to generate a profile of the energy consumption efficiency of the vehicle. The method further includes generating a signal to selectively adjust at least one of a speed of the vehicle, at least one route characteristic of a portion of a route being traversed by the vehicle, and a torque demand of the vehicle.

The disclosure generally pertains to recommending an alternative off-road track to a driver of a vehicle. In an example method, a processor receives a sensor signal that is generated in response to an operating condition of the vehicle on an off-road track. The operating condition can include, for example, an angular orientation of a chassis portion of the vehicle with respect to a ground surface (yaw, pitch, roll, etc.), steering characteristics, speed characteristics, and/or braking characteristics. The processor evaluates the sensor signal to identify an attribute of the off-road track, such as, for example, a difficulty factor and/or a challenge level. The processor may assign a track score to the off-road track based on the attribute and may provide to the driver, a recommendation for use of another off-road track based on comparing the first track score to a second track score associated with the other off-road track.

The disclosure generally pertains to recommending an alternative off-road track to a driver of a vehicle. In an example method, a processor receives a sensor signal that is generated in response to an operating condition of the vehicle on an off-road track. The operating condition can include, for example, an angular orientation of a chassis portion of the vehicle with respect to a ground surface (yaw, pitch, roll, etc.), steering characteristics, speed characteristics, and/or braking characteristics. The processor evaluates the sensor signal to identify an attribute of the off-road track, such as, for example, a difficulty factor and/or a challenge level. The processor may assign a track score to the off-road track based on the attribute and may provide to the driver, a recommendation for use of another off-road track based on comparing the first track score to a second track score associated with the other off-road track.

A system for controlling an internal combustion engine start threshold in a parallel hybrid-electric vehicle. A predetermined conditions tracking module determines whether or not conditions of a plurality of predetermined conditions exist. Responsive to a determination that the conditions exist, a required power estimation module estimates a next acceleration required by the vehicle and a final power requirement for the next acceleration. A propulsion system control module determines if the estimated final power requirement is between a first amount of electric motor power available at a predetermined base engine start threshold and a second amount of electric motor power available at a predetermined elevated engine start threshold. If the estimated final power requirement is between the first and second amounts of power, operation of the vehicle is controlled so as to ensure that the engine start threshold is at the predetermined elevated threshold.

The invention relates to a method for predictively generating data for controlling a drive track and an operating sequence of an agricultural vehicle and of an agricultural machine, the method comprising the steps automatically detecting and storing vehicle and/or machine data through a sensor arrangement that is arranged at individual vehicles or individual machines for generating a vehicle and machine model; collecting and storing data regarding a three dimensional terrain topography and/or data regarding current and/or forecasted terrain properties and/or a weather condition for generating a predictive three dimensional geo referenced terrain model; optimizing imaging of the vehicle and machine model into the three dimensional predictive terrain model and computing drive track control data for defining a drive track and/or machine control data for controlling machine components; putting out and transmitting the drive track control data and/or the machine control data to a control unit of the agricultural vehicle and/or agricultural machine.

The invention relates to a method for predictively generating data for controlling a drive track and an operating sequence of an agricultural vehicle and of an agricultural machine, the method comprising the steps automatically detecting and storing vehicle and/or machine data through a sensor arrangement that is arranged at individual vehicles or individual machines for generating a vehicle and machine model; collecting and storing data regarding a three dimensional terrain topography and/or data regarding current and/or forecasted terrain properties and/or a weather condition for generating a predictive three dimensional geo referenced terrain model; optimizing imaging of the vehicle and machine model into the three dimensional predictive terrain model and computing drive track control data for defining a drive track and/or machine control data for controlling machine components; putting out and transmitting the drive track control data and/or the machine control data to a control unit of the agricultural vehicle and/or agricultural machine.

The disclosure relates to a method for operating a hybrid electric vehicle. According to the method, a route information is received in the form of a plurality of parameter sets, each parameter set relating to a segment of a route (S1). Subsequently, a power demand is estimated for each segment (S3) and a portion of an amount of energy being stored in the electric storage device is allocated to at least one of the segments. Alternatively or additionally, an amount of energy to be transferred into the electric storage device is allocated to at least one of the segments (S4). Additionally, at least one reference trajectory describing a state-of-energy of the electric storage device over the route resulting from the energy allocation is derived (S5). The operation of the hybrid electric vehicle is controlled as a function of a slope between a current state-of-energy and an upcoming control point on the reference trajectory (S7). Moreover, a data processing device comprising means for carrying out the method is presented.