A driving force control system according to an embodiment of the present invention includes: an absolute bank angle detector configured to detect an absolute bank angle that is the absolute value of a vehicle's bank angle; a calculation circuit configured to calculate a relative bank angle that is the vehicle's relative angle with respect to a maximum absolute bank angle that is the maximum value of the absolute bank angle; and a controller configured to control driving force based on the relative bank angle.

A vehicle body speed estimation device and a vehicle body speed estimation method are provided for estimating a vehicle body speed of a four-wheel drive vehicle from a wheel speed of each wheel of the four-wheel drive vehicle. In the vehicle body speed estimation device and a vehicle body speed estimation method, a controller determines whether a deviation of at least two of the wheel speeds among the wheel speeds is within a first prescribed range. The controller switches a method for selecting the wheel speed used for estimating the vehicle body speed between a first method and a second method when a sign of a drive torque that is applied to each of the wheels is reversed and the deviation of at least two of the wheel speeds among the wheel speeds is within the first prescribed range.

A method for predicting, for a motor vehicle traveling on a first road segment, a future coefficient of friction of the vehicle on a second road segment. The method includes steps of obtaining operating parameters of the vehicle and at least one characteristic of the first road segment, of computing an indicator on the basis of the obtained operating parameters of the vehicle, of determining a frictional category of the vehicle according to the value of the computed indicator and of the at least one obtained characteristic of the road segment, of selecting a friction profile of the vehicle on the basis of the determined frictional category, and of determining a coefficient of friction of the vehicle by applying the selected profile to at least one characteristic of the second road segment. A device for implementing the prediction method is also disclosed.

A road surface inclination angle calculation device includes a storage device configured to store mapping data that prescribes mapping, and an execution device. The mapping includes a front-rear acceleration variable and a drive wheel torque variable as input variables, and includes, as an output variable, an inclination angle variable that is a variable indicating the inclination angle of a road surface, on which a vehicle is traveling, for the travel direction of the vehicle. The execution device is configured to acquire the values of the input variables, and configured to calculate the value of the output variable by inputting the acquired values of the input variables to the mapping.

Systems and methods are provided for controlling a hybrid powertrain of a hybrid vehicle, and may include: determining a value of a drive request for a combustion engine of the hybrid vehicle; determining electrical loading on batteries of the hybrid vehicle; adjusting operation of an accessory of the hybrid vehicle to reduce the electrical load of that accessory on the batteries of the hybrid vehicle when the drive request value is above a determined drive request threshold amount and the electrical loading on batteries of the hybrid vehicle is above a power loading threshold; and directing at least some of the power saved by adjusting operation of the accessory from the batteries of the hybrid vehicle to a drive motor of the hybrid vehicle to provide motive force for the vehicle.

The present invention relates to a method for having a vehicle (100) follow a desired curvature path (C1), said vehicle (100) comprising at least one differential (10, 20, 30) with a differential lock connected to at least one driven wheel axle (40, 50) of said vehicle (100), said method comprising at least the following steps: —providing (S1) information regarding state of said differential lock, said state being either that said differential lock is activated or unlocked, and when said differential lock is activated: —calculating (S2) a yaw moment, M.sub.diff, of said vehicle (100), caused by said differential lock; and —compensating (S3) for a deviation from said desired curvature path (C1) caused by said yaw moment, M.sub.diff, such that a resulting steering angle is equal to or less than a maximum allowed steering angle of said vehicle (100), whereby said compensation is a feed forward compensation. The invention also relates to a control unit, a vehicle, a computer program and a computer readable medium.

A method for monitoring at least one bearing of a motor vehicle which has the bearing and at least one electric machine, and can be operated by the electric machine supplying the electric machine with alternating electric current which is made available by power electronics, assigned to the electric machine, of the motor vehicle, as a result of which the electric machine is operated as an electric machine, by which the motor vehicle is operated, detecting the alternating current, made available by the power electronics, by at least one alternating current sensor; determining at least one torque which is made available by the electric machine in order to drive the motor vehicle, in accordance with the detected alternating current; and monitoring the bearing in accordance with the determined torque.

A method for controlling autonomous driving in an autonomous vehicle includes detecting a situation in which autonomous driving is impossible while the vehicle operates in an autonomous driving mode, outputting a control-right handover request warning alarm and then activating a minimal risk maneuver driving mode, determining a human driver gaze validity based on the detected situation, determining a human driver intervention validity upon determination that the human driver gaze is valid, and determining control-right handover of the autonomous vehicle based on the human driver intervention validity. Thus, the control-right may be reliably transferred from a system to a human driver.

A system comprising a computer including a processor and a memory, the memory including instructions such that the processor is programmed to: determine whether a difference between a friction coefficient label and a determined friction coefficient corresponding to an image depicting a surface is greater than a label threshold; modify the determined friction coefficient to equal the friction coefficient label when the difference is greater than the label threshold; and retrain a neural network using the image and the friction coefficient label.

A system for lateral control in-path tracking of an autonomous vehicle includes a lateral controller. The lateral controller controls movement of the autonomous vehicle relative to a path and receives as an input a desired target. An outer control loop of the lateral controller includes a first controller generating an output based on the difference between the desired target and a current position of the autonomous vehicle. An inner control loop of the lateral controller includes a second controller receiving the generated output from the first controller. The inner control loop generates a sideslip angle and a yaw rate, wherein the sideslip angle and the yaw rate are returned to the second controller. The sideslip angle and the yaw rate are used to generate the relative yaw angle and lateral distance, which are returned to the first controller as the current position of the autonomous vehicle.