Abstract: A method for carrying out a closing operation of a closing part device of a vehicle driven by an electric motor drive unit is disclosed. The method has the following steps: ascertaining friction force data that represent a current stiffness of the closing device using a machine learning method that has been trained with reference friction force data from past closing operations as input data, wherein the input data are transmitted to a server apparatus that is configured to ascertain the friction force data using the machine learning method, ascertaining target drive power data, taking the friction force data into consideration, for the drive unit, and operating the drive unit based on the ascertained target drive power data to carry out the closing operation in at least one subsequent closing operation.

Abstract: A method for determining the rotational speed and the angle of rotation of a motor shaft of a mechanically commutated DC motor from the measured progression of time of the ripple in the motor current and in the motor terminal voltage occurring during the commutation. A motor state model of the DC motor, to which the measured motor terminal voltage and the measured motor current, an estimated load torque, an estimated rotational speed and an estimated angle of rotation of the DC motor are supplied to a Kalman filter as input variables. By running the motor state model, the Kalman filter provides an estimated current, an adjusted rotational speed and an adjusted angle of rotation of the DC motor as output variables.

Abstract: A method for determining the rotational speed and the angle of rotation of a motor shaft of a mechanically commutated DC motor from the measured progression of time of the ripple in the motor current and in the motor terminal voltage occurring during the commutation. A motor state model of the DC motor, to which the measured motor terminal voltage and the measured motor current, an estimated load torque, an estimated rotational speed and an estimated angle of rotation of the DC motor are supplied to a Kalman filter as input variables. By running the motor state model, the Kalman filter provides an estimated current, an adjusted rotational speed and an adjusted angle of rotation of the DC motor as output variables.