A performance dimension is selected, and a gap in machine performance, according to the selected dimension, is identified. A target value is identified to improve machine control according to the selected dimension. A dependent dimension, which depends on the selected dimension, is selected and a dependency indicator, that indicates a dependency of the dependent dimension on the selected dimension, is accessed to identify a value of the dependent dimension that will change if the machine is controlled so that the value of the selected dimension is moved from a current value to the target value. The change in value of the selected dimension, and the dependent dimension are aggregated to determine whether machine control should be modified so the value of the selected dimension moves toward the target value. If so, a corresponding control operation is identified, and control signals are generated to control the machine to perform the identified control operation.

A tire force estimation system includes a sensor, a sensor information acquisition unit, and a tire force calculator. The sensor measures a physical quantity of a tire. The sensor information acquisition unit acquires the physical quantity measured by the sensor. The tire force calculator includes an arithmetic model for calculating tire force F based on the physical quantity, and calculates the tire force F by inputting the physical quantity acquired by the sensor information acquisition unit into the arithmetic model.

A system includes a computer including a processor and a memory, the memory storing instructions executable by the processor to plan a plurality of vehicle speeds for an upcoming road segment, adjust one or more of the planned speeds based on a predicted torque loss including a penalty based on a predicted torque impeller speed, and actuate a propulsion according to the planned speeds to lock a torque converter clutch.

An arithmetic model generation system includes a sensor information acquisition unit, a tire force calculator, and an arithmetic model update unit. The sensor information acquisition unit acquires acceleration of a tire. The tire force calculator includes an arithmetic model for calculating tire force F based on the acceleration, and calculates the tire force F by inputting the acceleration acquired by the sensor information acquisition unit. The arithmetic model update unit compares tire axial force measured by the tire and the tire force F calculated by the tire force calculator, and updates the arithmetic model.

A failure diagnostic system includes an instrument and a failure diagnostic device. The instrument makes measurement of a measured value regarding behavior of a diagnosis target. The failure diagnostic device has a model of the diagnostic target and performs simulation based on the model. The failure diagnostic device offers a user a proposal for execution of a special operation on the diagnostic target, on the condition that a difference between a result of the simulation and the measured value is greater than a predetermined error range but the difference provides an insufficient basis to determine whether or not the diagnosis target has a failure. The result of the simulation is calculated with the model supplied with a same input as an input to the diagnosis target at the time of the measurement by the instrument of the measured value regarding the behavior of the diagnosis target.

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.

A method for managing a powertrain (3) of a motor vehicle (1) comprises the following steps: (a) determining a predictive rolling resistance coefficient (Crr) for at least one tyre (10) of the motor vehicle (1); and (b) adapting the operation of the powertrain (3) according to the predictive rolling resistance coefficient (Crr) in order notably to optimize the energy consumption of the motor vehicle (1).

A distributed system for monitoring and control of a vehicle includes a supervisory controller with a first computer readable storage media for monitoring and storing a plurality of operational parameters regarding a physical system of the vehicle. The supervisory controller communicates with a server via two different communications networks. Method steps are provided for characterizing and predicting functional details of a system state of the physical system using the model parameters and at least one operational parameter of the physical system, and for using values obtained by the server regarding a plurality of different vehicles in order to improve the monitoring and control of the vehicle. A method is also provided to determine and report any operational parameters miss a corresponding performance target. A method is also provided for changing the storage or transmission of operational parameters based on their relative importance.

A device for estimating a condition of a road surface on which a tire is travelling, the device including: an acceleration sensor 11 that detects acceleration in a tire radial direction, an acceleration waveform extracting unit 12 that extracts an acceleration waveform from the acceleration, a differential waveform calculating unit 13 that calculates a differential waveform of the acceleration waveform, a rotation time calculating unit 14 that calculates a rotation time of the tire from the differential waveform, a normalized acceleration waveform generating unit 15 that generates a normalized acceleration waveform by using the rotation time, and a road surface condition estimating unit 16 that determines whether or not a water infiltration condition between the tire and the road surface is in a condition to be shifted to a hydroplaning condition.

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 position of a left lane delimiter on the road on a left side of the vehicle and position of a right lane delimiter on the road on a right side of the vehicle. The controller is operable to determine a target path for the vehicle based on processing 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. The lane centering system may be enabled responsive to the vehicle speed exceeding a threshold speed, and may be disabled during a braking event of a collision mitigation system of the vehicle.