Mutuwo Tomita

An extended electromotive force model for sensorless control of interior permanent-magnet synchronous motors

During the last decade, many sensorless control methods have been proposed for surface permanent-magnet synchronous motors (SPMSMs) based on the estimation of electromotive force (EMF) in which the motors position information is contained. However, these methods cannot be applied to interior PMSMs (IPMSMs) directly, because the position information is contained in not only the EMF, but also the inductance of stators. In this paper, a new mathematical model for IPMSMs is proposed and an extended EMF is defined, which includes both position information from the EMF and the stator inductance. By using the newly proposed model, sensorless controls proposed for SPMSMs can easily be applied to IPMSMs. As an example, a disturbance observer is studied and the experimental results show that the proposed method on the proposed model is very effective.

Sensorless control of permanent-magnet synchronous motors using online parameter identification based on system identification theory

An online parameter identification method and sensorless control using identified parameters were realized in surface and interior permanent-magnet synchronous motors (SPMSMs and IPMSMs, respectively). As this method does not use rotor position or velocity to identify motor parameters, the identified parameters are not affected by position estimation error under sensorless control. The proposed method can be applied to all kinds of synchronous motors. The effectiveness of the proposed method was verified by experiments in both SPMSMs and IPMSMs.

New sensorless control for brushless DC motors using disturbance observers and adaptive velocity estimations

A brushless DC motor has been represented by a nonlinear equation. Therefore, it has been difficult to apply linear control theory to brushless DC motor systems. In this paper, to apply the linear control theory to brushless DC motor systems, the authors propose considering the nonlinear term of the equation as a disturbance and to realize a sensorless control of the brushless DC motor using both the disturbance observer and the adaptive velocity estimation. With proper pole locations of the disturbance observer, stability of the position estimation is guaranteed, and stability of the adaptive velocity estimation is also guaranteed by Popovs hyperstability theory. The experimental results show that the proposed method is very useful.

New adaptive sliding observers for position- and velocity-sensorless controls of brushless DC motors

A new adaptive sliding observer is proposed for position- and velocity-sensorless controls of a cylindrical brushless DC motor. Stability of the proposed observer is guaranteed easily, because it is based on a linear model of the motor. Sliding mode is applied for the current estimation. Under the sliding mode, the order of the observers error equation is reduced. This makes the stability analysis easier, so that robust position and velocity estimations might be achieved by the pole assignment. Experimental results show that the proposed method is very effective.

Sensorless Control of Synchronous Reluctance Motors Based on Extended EMF Models Considering Magnetic Saturation With Online Parameter Identification

A sensorless control method based on novel extended electromotive force (EEMF) models considering magnetic saturation is proposed for synchronous reluctance motors (SynRMs). Since motor parameters, particularly inductances, vary largely in SynRMs, a precise sensorless control is necessary for fully considering such variations. In this paper, the EEMF model, taking into consideration magnetic saturation, is derived and is applied to a position estimation method. The two EEMF models caused by a difference in the d-axis direction are shown, and the appropriate EEMF model that can suppress a position estimation error caused by the deviation of inductance parameters is proposed. Moreover, an online parameter identification method for sensorless control in middle- or high-speed ranges is proposed. The necessity for the use of the model, taking into consideration magnetic saturation, is verified by experiments. The proposed sensorless control system is shown useful by experiments

Sensorless control of an interior permanent magnet synchronous motor on the rotating coordinate using an extended electromotive force

Permanent magnet synchronous motors have been widely used in industrial applications for their high efficiency. To control permanent magnet synchronous motors, knowledge of rotor position and velocity is necessary. However, position sensors are expensive and mechanically bulky. Although many sensorless control methods have been proposed, but these schemes used approximations for simplification of the mathematical model, which may lead to unstable problems at certain conditions. To solve this problem, the sensorless control based on an extended electromotive force model has been proposed in this paper. The proposed method has been verified by experiments.

Sensorless estimation of rotor position of cylindrical brushless DC motors using eddy current

A rotor position estimation of a cylindrical brushless DC motor at a standstill has been difficult, and the realization has been desired. This paper proposes a simple processing of a rotor by pasting non-magnetic materials where eddy currents can flow on the rotor surface. This process causes a change of amplitude of the phase current according to the rotor position. The experimental results show that the rotor position estimation with maximum error of 26/spl deg/ electrical angle has been realized, which is useful for 120/spl deg/ conduction type cylindrical brushless DC motors.

Initial position estimation and low speed sensorless control of synchronous motors in consideration of magnetic saturation based on system identification theory

We propose a novel method for estimating the initial position and achieving low-speed sensorless control of synchronous motors based on system identification theory. We derive mathematical models that consider magnetic saturation, and use this model for position estimation. The proposed method requires neither any band-pass filters nor motor parameters, and it can be applied to all kinds of synchronous motors without any tuning. Polarity detection of the magnetic pole can be also determined simultaneously with position estimation, making extra signals for polarity detection unnecessary. The proposed estimation method is verified experimentally.

Position and velocity sensorless control of SynRMs using on-line parameter identification

This paper presents a novel on-line parameter identification system for position sensorless control of synchronous reluctance motors (SynRMs). The proposed identification system can identify motor parameters in position sensorless control. Therefore, there is no necessity of complicated measurements of motor parameters in advance. Under position sensorless control, since the mathematical model includes the position and velocity whose actual value is unknown, the estimated position and velocity are substituted for them. As a result, there is a possibility that identified parameters can be affected by the position and velocity estimation error. However, since the proposed system cancels position and velocity terms, identified parameters are not affected by them. The position sensorless control using identified motor parameters is realized, and the effectiveness of proposed system is verified by experimental results.

Low speed sensorless control and initial position estimation of synchronous reluctance motors based on system identification theory

In this paper, we propose a position estimation method for synchronous reluctance motors in standstill and low-speed ranges. We derive a mathematical model considering magnetic saturation and an estimation method using this model. The proposed method is based on the system identification theory and uses the relation between voltages and currents of a mathematical model. Since the proposed method can estimate rotor position from only voltages and currents, any motor parameters are not necessary at all and estimated position are not affected by variation of motor parameters. Additionally, the proposed method can use information of all frequency band. Therefore, any band-pass filters are not necessary The proposed estimation method is verified by experiments.