Device (1) and method for detecting battery cell states, BZZ, and/or battery cell parameters, BZP, of at least one battery cell (BZ), comprising a dual Kalman filter (2) which includes a state estimator (2A) for estimating battery cell states, BZZ, and a parameter estimator (2B) for estimating battery cell parameters, BZP, and comprising a determination unit (3) which is suitable for determining noise components (n, v) of the state estimator (2A) and of the parameter estimator (2B) on the basis of a stored characteristic parameter behaviour of the battery cell (BZ), wherein the battery cell states, BZZ, and the battery cell parameters, BZP, can be adapted automatically to a specified battery model (BM) of the battery cell (BZ) by means of the dual Kalman filter (2) on the basis of the noise components (n, v) determined by the determination unit.

An object of the present invention is to provide a motor control device capable of estimating a delay with high accuracy even in a case where there is a fluctuation in disturbance torque or delay time and of suppressing the influence of the delay. For this end, the present invention includes a motor MTR, an ECU 2 that controls the rotation of the motor MTR, and an ECU 1 that sends a torque command to the ECU 2 based on a command value. The ECU 1 includes a disturbance estimation block 100 and a delay estimation block 200. The disturbance estimation block 100 estimates disturbance torque (?d) using a torque command input to the ECU 2 and a feedback value of the motor MTR. The delay estimation block 200 estimates a delay using a torque command output from the ECU 1, the feedback value of the motor MTR, and the disturbance torque (?d).

Methods and apparatuses for determining operational parameters of a blood pump comprising a rotor which transports the blood are provided. The change in the behaviour of at least one first and one second operational parameter, independently from each other, of the pump, is determined. A determination of the flow through the pump and/or the difference in pressure across the pump and/or the viscosity of the blood takes into account the determined change in behaviour of the at least two operational parameters. A modelling for a dynamic model of the known quantities may be carried out and an estimation method using a Kalman filter may be used.

The disclosure provides a method for controlling a drive arrangement for a flap of a vehicle by a control arrangement, wherein in a measuring routine a measured movement value is measured by a movement measuring system. It is proposed that in an estimation routine an estimated movement value is estimated, in a movement routine the estimated movement value is determined via the estimation routine and the flap is adjusted according to a set movement value, in a correction routine the estimated movement value is determined from the estimation routine and an estimation error is determined and from the estimated movement value and according to a correction specification the set of model parameters is corrected based on the estimation error and supplied to the estimation routine and in the correction routine the correction of the set of model parameters is performed for a part section of the motorized movement cycle.

According to embodiments described herein, there is provided methods and apparatus for providing a driving signal to a transducer, wherein the driving signal is output by an amplifier. A method comprises receiving an indication of a voltage and a current of the driving signal; based on an electrical model of the transducer and the voltage and the current of the driving signal, estimating an estimated electrical response of the transducer representative of movement of a mass in the transducer; comparing the estimated electrical response to a desired electrical response; and controlling the driving signal based on the comparison.

This disclosure describes techniques for providing a transformative framework to forecast physical properties of an atmosphere to predict the orbit of satellite devices. As one example, the transformative framework has two major components: (i) the development of a quasi-physical dynamic reduced-order model (ROM) that uses a linear approximation of the underlying dynamics (e.g., solar conditions or magnetic conditions) and effect of the drivers, and (ii) data assimilation and calibration of the ROM through estimation of the ROM coefficients that represent the model parameters.

A method determines the total mass of an automotive vehicle on the basis of data of a communication network and parameters of the vehicle, in which an estimation of the total laden mass (mv,est) of the vehicle, of the speed of the vehicle (vest) and of the slope of the road (est) is determined at an instant (k) by applying the fundamental equation of dynamics and as a function of the values of the total mass of the vehicle, of the speed of the vehicle and of the slope of the road at a previous instant (k1).

Methods and apparatuses for determining operational parameters of a blood pump comprising a rotor which transports the blood are provided. The change in the behaviour of at least one first and one second operational parameter, independently from each other, of the pump, is determined. A determination of the flow through the pump and/or the difference in pressure across the pump and/or the viscosity of the blood takes into account the determined change in behaviour of the at least two operational parameters. A modelling for a dynamic model of the known quantities may be carried out and an estimation method using a Kalman filter may be used.

The invention relates to the real-time determination of the forces applied by waves incident upon the moving part (2) of a wave-energy system (1). The method according to the invention is based on the construction of a model of the radiation force applied to the moving part (2) and a model of the dynamics of the wave-energy system (1). The invention uses only measurements of the kinematics of the moving part (2) and the force applied by the conversion machine (3) to the moving part (2).

A signal processing device includes a Kalman filter that performs Kalman filter processing based on an observation noise and a system noise and outputs a DC component of an input signal as an estimated value; and a monitoring circuit. The Kalman filter outputs an error covariance of the estimated value. The monitoring circuit performs a stop command of observation update processing in the Kalman filter, based on a result of determination processing based on the error covariance, with respect to a signal level corresponding to the input signal.