A method of controlling a permanent magnet synchronous electric machine (PMSM) drive using a Deadbeat Predictive Current Control (DBPCC) scheme is provided. The method comprises: determining d-axis and q-axis stator current values (i.sub.d, i.sub.q) representative of a measured PMSM current; determining d-axis and q-axis reference current values (i.sub.d*, i.sub.q*); based on the stator current values (i.sub.d, i.sub.q) and the reference current values (i.sub.d*, i.sub.q*), determining d-axis and q-axis current correction values (C.sub.d, C.sub.q); determining corrected reference current values (i.sub.d**, i.sub.q**) as a sum of the reference current values (i.sub.d*, i.sub.q*) and the current correction values (C.sub.d, C.sub.q); and controlling the PMSM drive using the corrected reference current values (i.sub.d**, i.sub.q**) as reference current inputs of the DBPCC scheme. A controller for performing the method; a system comprising the controller, a PMSM and associated power electronics; and a computer program for performing the method are also provided.

An electric machine is provided. A polyphase machine is provided. A power inverter is electrically connected to the polyphase machine. A controller is electrically connected to the power inverter, wherein the controller provides switching signals to the power inverter, wherein the controller comprises a trajectory calculator that provides an optimized trajectory for transitioning the polyphase machine from a first torque to a second torque.

An electronic device includes an artificial intelligence processor that is configured to generate second information for controlling an electric component including at least one of a drive unit that applies propulsion force to a human-powered vehicle, an electric adjustable seatpost, and an electric suspension in accordance with first information related to at least one of the human-powered vehicle, a rider of the human-powered vehicle, and an environment of the human-powered vehicle. The artificial intelligence processor changes a process for generating the second information in accordance with the first information and in accordance with an operation of a first operation unit for operating the at least one of the drive unit, the electric adjustable seatpost, and the electric suspension.

A human-powered vehicle control device includes an artificial intelligence processor, an operation device, and a communication device. The artificial intelligence processor is configured to generate second information for controlling an electric component of a human-powered vehicle in accordance with first information related to at least one of the human-powered vehicle, a rider of the human-powered vehicle, and an environment of the human-powered vehicle. The operation device operates the electric component. The communication device is configured to communicate with an external device. The artificial intelligence processor is configured to change a process for generating the second information in accordance with the first information and an operation of the operation device. The communication device is configured to transmit third information related to a process for generating the second information to the external device.

A method ascertains current-dependent inductances of a polyphase electrical machine. The method generates phase voltages for the polyphase electrical machine by means of a pulse width modulation such that currents of predefined current level flow through stator windings of the electrical machine. During a number of cycles of the pulse width modulation, the method generates a voltage pulse such that a change of current is brought about in a torque-forming axis of the polyphase electrical machine and/or in a field-forming axis of the polyphase electrical machine. The method measures the change of current, and ascertains the current-dependent inductances on the basis of the change of current.

A method of speed control based on a self-learning model of load torque and a moment inertia is applied to a controller of controlling a motor. The method includes steps of: establishing a relationship between the load torque and the moment inertia by a self-learning manner, correspondingly acquiring a value of the moment inertia according to a value of the load torque, and adjusting parameters of the controller to control rotation of the motor according to the value of the moment inertia.

A control device includes: a current detector that detects rotating electrical machine currents flowing to the rotating electrical machine; a position estimator that estimates a rotor position of the rotating electrical machine based on the rotating electrical machine currents; a controller that calculates drive voltage commands based on the rotating electrical machine currents and information on the rotor position, adds position estimation voltage commands and the drive voltage commands to obtain rotating electrical machine voltage commands. The position estimator extracts position estimation currents included in the rotating electrical machine currents, the position estimation currents being changed according to the position estimation voltage commands, and estimates the rotor position of the rotating electrical machine using a DC component of amplitudes of the position estimation currents extracted, the DC component being not changed according to the rotor position.

An apparatus according to the aspect of the embodiments includes a phase determiner configured to determine a rotational phase of a rotor, a speed determiner configured to determine a rotational speed of the rotor, a controller having a first control mode for controlling the motor by supplying constant currents to windings, and a discriminator configured to discriminate whether a rotation of the motor is abnormal based on the rotational speed when the rotational speed corresponding to a command speed is equal to or higher than a predetermined value in a state where the controller is controlling the motor in the first control mode. When a signal output from the discriminator indicates that the rotation of the motor is abnormal, the controller stops the motor. When the signal output from the discriminator indicates that the rotation is not abnormal, the controller continues a drive of the motor.

A motor control actuator that drives a permanent magnet synchronous motor (PMSM) with sensorless Field Oriented Control includes a sampling circuit that generates a measurement signal by measuring a back electro motive force (BEMF) of the PMSM, while the PMSM rotates; a PLL that receives the measurement signal and extracts an amplitude and an angle of the BEMF from the measurement signal; and a motor controller that generates a first set of two phase alternating current (AC) voltage components based on an estimated rotor angle, generates a second set of two phase AC voltage components based on the amplitude and the angle, and generates control signals for driving the PMSM based on the first set of two phase AC voltage components. The motor controller performs a catch spin sequence for restarting the PMSM while rotating, the catch spin sequence includes a synchronizing period followed by a closed loop control period.

A motor drive apparatus includes: a dq-axis current controller converting phase current flowing through a synchronous motor into d-axis current and q-axis current, and controlling the phase current by determining a voltage command based on the d-axis current and a d-axis current command as well as the q-axis current and a q-axis current command; a voltage amplitude calculating unit obtaining voltage amplitude; a speed controller controlling rotational speed of the motor by determining the q-axis current command based on a speed command, the rotational speed, and a speed droop amount that reduces the speed command; a flux weakening controller performing flux control to limit amplitude of voltage output to the motor by determining the d-axis current command based on the voltage amplitude and a first voltage limit value; and a speed droop controller controlling the speed droop amount based on the voltage amplitude and a second voltage limit value.