Disclosed is a system for estimating the speed of a vehicle. The system includes a plurality of wheel rotation sensors, a grade sensor, an acceleration sensor, an accelerator pedal deflection sensor, a brake pedal deflection sensor, and a processor. The processor is configured to compute a linear wheel speed, an upper limit of vehicle speed, and a lower limit of vehicle speed, based on the grade information, the pedal deflection information, and the acceleration, and then compute an estimated speed of the vehicle based on the linear wheel speed, the upper limit of vehicle speed, and the lower limit of vehicle speed.

The present disclosure discloses a control method and device for automated guided vehicle, and automated guided vehicle. By utilizing the coupling relation between the turntable and the chassis, a disturbance to the chassis electromechanical control subsystem is compensated by using a feedback signal in the turntable electromechanical control subsystem, or a disturbance to the turntable electromechanical control subsystem is compensated by using a feedback signal in the chassis electromechanical control subsystem, so that high-precision movement control of the turntable and the chassis is realized.

Fuzzy-logic based traction control for electric vehicles is provided. The system detects a wheel slip ratio for each wheel. The system receives an input torque command. The system determines a slip error for each wheel based on the wheel slip ratio for each wheel and a target wheel slip ratio. The system, using the fuzzy-logic based control selection technique, selects a traction control technique from one of a least-quadratic-regulator, a sliding mode controller, a loop-shaping based controller, or a model predictive controller. The system generates a compensation torque value for each wheel. The system generates the compensation torque value based on the traction control technique selected via the fuzzy-logic based control selection technique and the slip error for each wheel. The system transmits commands to actuate drive units of the vehicles based on the compensation torque value.

Methods and systems are provided for adjusting driver demand wheel torque of a vehicle. The driver demand wheel torque may be adjusted as a function of a minimum wheel torque. The minimum wheel torque may be determined according to a plurality of torques that may be evaluated in three different phases.

Methods and systems for monitoring and determining a propulsion request are described. In one example, the propulsion request is evaluated according to two separate plausibility checks. The plausibility checks may include comparing a monitor propulsion request against the propulsion request and comparing the monitor propulsion request against a wheel torque.

A torque vectoring system for a hub motor drive system uses a motor control unit instead of a vehicle control unit to conduct torque vectoring calculation, so that a target motor torque can be obtained more reasonably and the real-time property is improved. In addition, as it is unnecessary to conduct calculation with the vehicle control unit, torque distribution and torque change can be evaluated on a testbed of the motor control unit prior to integrating the torque vectoring system into the vehicle.

A control device of a vehicle includes a power transmission device transmitting a power of a power source to drive wheels, the control device comprises: a drive force limiting portion limiting a drive force of the vehicle by an upper limit value when the vehicle is running on a wavy road and a value representing a variation in a predetermined rotation speed of a drive system component disposed between the power source to the drive wheels is equal to or greater than a resonance determination value; an upper limit value setting portion setting the upper limit value to a value corresponding to the wavy road on which the vehicle is currently running, based on current position information indicative of a current position of the vehicle.

A method for assignment of vehicle control includes receiving route data indicating a route between a starting location of a vehicle and a destination location, and determining an optimal vehicle configuration for the route based on a target vehicle speed and a hybrid torque split. The method further includes receiving a driver requested torque value and determining a passive pedal torque value based on the route data and vehicle powertrain data. The method further includes selectively assigning control of the vehicle to a vehicle system or to a driver of the vehicle based on the driver requested torque value and the passive pedal torque value.

A method for controlling autonomous driving in an autonomous vehicle includes: determining whether a human driver is in a forward gaze state under an autonomous driving mode, setting a first steering wheel torque threshold and a first torque holding time, based on a result of determining whether the human driver is in the forward gaze state, determining whether human driver intervention has occurred, based on the first steering wheel torque threshold and the first torque holding time, and switching the autonomous driving mode to a manual driving mode when the human driver intervention has occurred.

A method for controlling actuators acting on vehicle wheels of a motor vehicle comprises ascertaining a force to be brought about on a reference point of the motor vehicle on the basis of driver specifications, ascertaining wheel forces to be brought about on the vehicle wheels to implement the force to be brought about on the reference point of the motor vehicle by means of a first dynamic allocation by model-based predictive control (MPC), ascertaining setpoint values for wheel parameters from the ascertained wheel forces, and actuating the actuators of the motor vehicle so as to implement the setpoint values of the wheel parameters.