Technical solutions are described for estimating tire-road friction in a vehicle pro-actively, prior to safety systems of the vehicle are engaged. An example method includes computing a slip for the vehicle based on one or more wheel speeds, acceleration, and tire pressure measurement. The method further includes determining a slope (α) as indicator of tire-road friction for the vehicle based on the acceleration and the slip. Further, the method includes sending the slope to an autonomous controller of the vehicle for adjusting vehicle kinematics according to the estimated friction using the slope.

Technical solutions are described for estimating tire-road friction in a vehicle pro-actively, prior to safety systems of the vehicle are engaged. An example method includes computing a slip for the vehicle based on one or more wheel speeds, acceleration, and tire pressure measurement. The method further includes determining a slope (α) as indicator of tire-road friction for the vehicle based on the acceleration and the slip. Further, the method includes sending the slope to an autonomous controller of the vehicle for adjusting vehicle kinematics according to the estimated friction using the slope.

A system and method for providing calibration data for driver assist systems based on a changed ride height includes receiving sensor data from at least one of a camera, RADAR sensor, ultrasonic sensor, and/or LiDAR sensor of the vehicle, determining that a ride height of the vehicle has changed based on the sensor data, retrieving calibration data for at least one driver assist system based upon the changed ride height; and operating the at least one driver assist system using the retrieved calibration data.

A system and method for providing calibration data for driver assist systems based on a changed ride height includes receiving sensor data from at least one of a camera, RADAR sensor, ultrasonic sensor, and/or LiDAR sensor of the vehicle, determining that a ride height of the vehicle has changed based on the sensor data, retrieving calibration data for at least one driver assist system based upon the changed ride height; and operating the at least one driver assist system using the retrieved calibration data.

The disclosure relates to a method to control torque distribution among a plurality of electric machines connected to at least one front wheel and at least one rear wheel of a vehicle during operation, comprising: acquiring the total torque requested; obtaining the most energy efficient torque distribution mode by using a loss model or loss map; evaluating the actual driving situation; determining if a mode switch is allowed depending on the actual driving situation; switching the torque distribution mode, if allowed; and preventing a mode switch, if not allowed.

The disclosure relates to a method to control torque distribution among a plurality of electric machines connected to at least one front wheel and at least one rear wheel of a vehicle during operation, comprising: acquiring the total torque requested; obtaining the most energy efficient torque distribution mode by using a loss model or loss map; evaluating the actual driving situation; determining if a mode switch is allowed depending on the actual driving situation; switching the torque distribution mode, if allowed; and preventing a mode switch, if not allowed.

An automotive vehicle includes an actuator configured to control vehicle steering, a sensor configured to detect a yaw rate of the vehicle, and a controller. The controller is configured to estimate a yaw rate and lateral velocity of the vehicle via a vehicle dynamics model based on a measured longitudinal velocity of the vehicle, calculated road wheel angles of the vehicle, and estimated tire slip angles of the vehicle. The controller is configured to receive a measured yaw rate from the sensor, and to calculate a difference between the measured yaw rate and the estimated yaw rate. The controller is configured to apply a model correction to the vehicle dynamics model using a PID controller based on the difference, and to estimate a vehicle position based on the estimated lateral velocity and the measured longitudinal velocity. The controller is configured to automatically control the actuator based on the vehicle position.

An automotive vehicle includes an actuator configured to control vehicle steering, a sensor configured to detect a yaw rate of the vehicle, and a controller. The controller is configured to estimate a yaw rate and lateral velocity of the vehicle via a vehicle dynamics model based on a measured longitudinal velocity of the vehicle, calculated road wheel angles of the vehicle, and estimated tire slip angles of the vehicle. The controller is configured to receive a measured yaw rate from the sensor, and to calculate a difference between the measured yaw rate and the estimated yaw rate. The controller is configured to apply a model correction to the vehicle dynamics model using a PID controller based on the difference, and to estimate a vehicle position based on the estimated lateral velocity and the measured longitudinal velocity. The controller is configured to automatically control the actuator based on the vehicle position.

A system is provided for evaluating vehicle performance. The system includes a function system model that models an operation of a function system of a vehicle and an operation of which is determined based on a control signal output from a controller within the vehicle. Additionally, the system includes a dynamic model configured to model a behavior of the vehicle based on the operation of the function system model.

A system is provided for evaluating vehicle performance. The system includes a function system model that models an operation of a function system of a vehicle and an operation of which is determined based on a control signal output from a controller within the vehicle. Additionally, the system includes a dynamic model configured to model a behavior of the vehicle based on the operation of the function system model.