A method for determining a motor angle, may include deriving a sensor weight and a sensorless weight via a cross product of an actual current vector and a model-based sensored current vector and a cross product of the actual current vector and a model-based sensorless current vector; and determining a final motor angle by applying the sensor weight and the sensorless weight to each of a sensored angle and a sensorless angle.

The invention relates to a method (400) for regulating an electric machine (190), comprising at least one first filter (140) and at least one second filter (142, 144). The method has the steps of: ascertaining (410) a feedback variable (Idq); filtering (412) a specifiable GW matching variable (Idq*); ascertaining (414) the filtered feedback variable without fundamental components (IdqWo-Funda); filtering (416) the filtered feedback variable without fundamental components (IdqWo-Funda); ascertaining (418) a filtered feedback variable without harmonic components (IdqFunda); and energizing (480) at least one winding of the electric machine (190) on the basis of the filtered feedback variable without harmonic components (IdqFunda).

The present invention discloses a control method of a dual three-phase permanent magnet synchronous motor by alternately performing sampling and control procedures, which belongs to the field of power generation, power transformation or power distribution technologies. Sampling instants, vector loading instants, and reference value tracking instants of two sets of windings alternate in two halves of a sampling period, and the equivalent sampling frequency of the motor drive system is doubled and the digital delay and the predictive horizon are halved without changing the sampling frequency of a single set of three-phase windings. In addition, by means of a two-layer MPC strategy, a deficient-rank problem is settled that the controlled dimensionality of the system is reduced to two dimensions but the motor control objective is still four dimensions caused by the method with controlling a dual three-phase permanent magnet synchronous motor by alternately performing sampling and control procedures. According to the control method of a dual three-phase permanent magnet synchronous motor by alternately performing sampling and control procedures provided in the present invention, the steady-state and dynamic control performance of a motor drive system for a dual three-phase permanent magnet synchronous motor is effectively improved, and computation burden of the control algorithm is reduced.

A method of calibrating a motor assembly includes selecting an electric motor and a motor controller for the motor assembly, obtaining at least one electric motor parameter of the electric motor, determining a correction factor for the electric motor based upon the at least one electric motor parameter, and programming the motor controller with the correction factor.

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 fuzzy finite-time optimal synchronization control method for a fractional-order permanent magnet synchronous generator, and belongs to the technical field of generators. A synchronization model between fractional-order driving and driven permanent magnet synchronous generators with capacitance-resistance coupling is established. The dynamic analysis fully reveals that the system has rich dynamic behaviors including chaotic oscillation, and a numerical method provides stability and instability boundaries. Then, under the framework of a fractional-order backstepping control theory, a fuzzy finite-time optimal synchronous control scheme which integrates a hierarchical type-2 fuzzy neural network, a finite-time command filter and a finite-time prescribed performance function is provided.

A controller for controlling a motor of a closure and/or blind in a vehicle body is configured to determine a reference state signal comprising speed and/or current measurements, repeatedly estimate motor model parameters of the motor, determine an estimated state signal based on an input signal comprising measurements or estimates of a voltage, the estimated motor model parameters, the reference state signal and an error signal, the error signal representing a difference between the reference state signal and the estimated state signal, determine a disturbance observer signal from the error signal, compute a first derivative of the disturbance observer signal at a present moment, and reverse the motor upon determining that the first derivative of the disturbance observer signal exceeds a threshold.

A method of calibrating a motor assembly includes selecting an electric motor and a motor controller for the motor assembly, obtaining at least one electric motor parameter of the electric motor, determining a correction factor for the electric motor based upon the at least one electric motor parameter, and programming the motor controller with the correction factor.

A method for model predictive current control of a two-motor torque synchronization system, which belongs to the field of power electronics and motor control. The present disclosure takes an indirect matrix converter and a two-motor system which are coaxially and rigidly connected as a target, and takes two-motor torque synchronization performance and current tracking performance as main control objectives. A two-motor unified prediction model is established and a value function based on free components of error items is configured so as to solve the problems in which when model predictive current control is performed on a two-motor system, setting of a value function weighting coefficient needs to be performed manually, and consequently the setting process is complicated and an erroneous switch state combination is likely to be selected.

A speed estimating device for an AC motor includes: a model deviation computing unit computing a model deviation based on a voltage, a current, and an estimated angular velocity of the AC motor; a first angular velocity estimating unit computing a first estimated angular velocity based on the model deviation; a second angular velocity estimating unit computing a second estimated angular velocity differing from the first estimated angular velocity in frequency, based on the model deviation; a compensation phase computing unit computing a compensation phase based on a disturbance frequency; and an estimated angular velocity calculator computing an estimated angular velocity of the AC motor based on the first estimated angular velocity and the second estimated angular velocity. Either one of the first estimated angular velocity and the second estimated angular velocity is computed based on the compensation phase.