A device diagnostic apparatus according to the present invention includes: a diagnosis model selecting unit that selects a diagnosis model for diagnosing a moving device in accordance with a driving environment of the device; and a diagnosis unit that inputs operation data of the device to the selected diagnosis model, receives an output of a diagnosis result for the device from the diagnosis model, and diagnoses the device.

The disclosure includes embodiments for modifying a performance of a vehicle component whose performance is affected by a vehicle fluid that is contaminated by water. A method according to some embodiments includes recording sensor data describing refractometry measurements for the vehicle fluid. The method includes determining contamination data that describes an amount of water present in the vehicle fluid. The method includes analyzing the contamination data to determine parameter data describing modifications for a set of parameters for an advanced driver assistance system (ADAS system) that control the operation of the ADAS system, wherein the parameter data is operable to update the set of parameters and thereby modify the operation of the ADAS system to compensate for the amount of water present in the vehicle fluid so that vehicle component performs as though the vehicle fluid is substantially not contaminated by water.

A method for operating a driver assistance system of a motor vehicle, which includes multiple wheels in contact with a roadway, the driver assistance system including at least one unit which includes a friction coefficient model and at least one sensor, which provides an input signal for the friction coefficient model, a friction coefficient between at least one of the wheels and the roadway being ascertained with the aid of the friction coefficient model, and the driver assistance system being set or calibrated as a function of the ascertained friction coefficient. Friction coefficients are ascertained with the aid of multiple of the units that ascertained friction coefficients are compared to one another, at least one valid friction coefficient of the friction coefficients is determined with the aid of the comparison, and the driver assistance system is set or calibrated as a function of the valid friction coefficient.

A method performed in a control unit of a heavy-duty vehicle for estimating road friction, the method comprising, while the vehicle is in motion, generating a steering pulse having a limited time duration and a limited magnitude, measuring a response by the vehicle to the steering pulse, and estimating a road friction value based on the measured response by the vehicle.

The present invention relates to an anti-jerk control apparatus and method for an Hybrid Electric Vehicle (HEV). The anti-jerk control apparatus includes a model speed calculation unit for calculating a model speed of the motor in a state in which a vibration of a drive shaft is not considered. A vibration occurrence determination unit detects a speed vibration component while calculating a reference speed difference and an average speed difference from differences between the model speed and an actual speed of the motor, thus determining whether a vibration occurs on the drive shaft. A torque correction value calculation unit calculates a motor torque correction value for anti-jerk required to damp the vibration of the drive shaft, and controls torque of the motor if the vibration occurrence determination unit determines that the vibration occurs on the drive shaft.

A steering application executing on a vehicle control module receives a steering control input to control a steered wheel of a vehicle. Based on the steering control input, the steering application determines a traction threshold value associated with a traction control attribute related to a traction wheel of the vehicle. A first diagnostic supervisor executing on the vehicle control module receives a measured value of the traction control attribute and the traction threshold value. When the measured value of the traction control attribute exceeds the traction threshold value, the first diagnostic supervisor repeatedly calculates a respective difference between the traction threshold value and the measured value of the traction control attribute to generate a set comprising a plurality of the respective differences. Based on the plurality of respective differences, the first diagnostic supervisor determines a first operating condition of a traction system of the vehicle.

A processor unit is configured for determining target torque values (21), which lie within a prediction horizon (20), and target speed values (19), which lie within the prediction horizon (20), by executing an MPC algorithm, which includes a longitudinal dynamics model of a drive train of the motor vehicle. An autonomous driving function of the motor vehicle is carried out in a torque specification operating mode or in a speed specification operating mode as a function of the level of the target torque values (21). In the torque specification operating mode, a prime mover of the drive train is controlled by an open-loop system based on the target torque values (21). In the speed specification operating mode, a speed governor of the drive train is controlled by an open-loop system based on the target speed values (19).

A lane centering system for use in a vehicle driving in a lane on a road includes a camera and a controller. Based on processing by a processor of image data captured by the camera, the controller determines the position of a left lane delimiter on the road on a left side of the vehicle and the position of a right lane delimiter on the road on a right side of the vehicle. The controller is operable to control a steering system of the vehicle that is configured to steer the vehicle. The controller is operable to determine a target path for the vehicle based on processing by the processor of image data captured by the camera. The determined target path maintains the longitudinal centerline of the vehicle centered between the left lane delimiter and the right lane delimiter.

To keep plant performance constant in a control apparatus for controlling a plant including a plurality of units. The control apparatus (a PCM) controls an automobile including a plurality of units. The control apparatus includes a model controller that generates a target value of a characteristic to be achieved by each unit based on a model set for each unit, a unit specifier (a performance change determinator) that specifies a unit in which performance unique to the unit has changed among the units, and a target value corrector (an FF updater) that corrects the target value for the unit that has been specified by the unit specifier.

A control system (10) is suitable for use in one's own motor vehicle (12) and is set up and intended to determine the current driving situation of one's own motor vehicle (12) and other motor vehicles (28, 40) in the surroundings of one's own motor vehicle (12) by means of a surroundings sensor system and to assign the other motor vehicles (28, 40) to specific movement paths or not. The control system is set up and intended based on the surroundings data provided to determine at least one path property for a future movement path of one's own motor vehicle (12), based on the surroundings data provided for every other motor vehicle (28, 40) in the surroundings of one's own motor vehicle (12) and in relation to at least two reference points of the respective other motor vehicle (28, 40) to determine a state vector, to transform the respectively determined state vector for each of the other motor vehicles (28, 40) into path coordinates and based on the at least one path property for one's own motor vehicle (12) and, to determine based on the respective transformed state vector, a probability distribution of a position of each of the other motor vehicles (28, 40) corresponding to each of the at least two reference points of the respective other motor vehicle (28, 40).