• Journal of Aerospace System Engineering
• /
• v.17 no.6
• /
• pp.100-107
• /
• 2023

Open-phase fault in a Permanent Magnet Synchronous Motor (PMSM) occurs due to disconnection of phases of motor windings or inverter switch failures. When an open-phase occurs, it leads to the generation of torque ripples and vibrations in the motor, which can have a critical impact on the safety of the vehicle (including aircraft) using a PMSM as an actuator. Therefore, rapid fault detection and classification are essential. This paper proposes a classification method for detecting open-phase faults and locating fault positions in a PMSM used in aircraft applications. The proposed approach uses an Extended Kalman Filter for fault diagnosis, and it subsequently classifies faults using a Multiple Model filter.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.67 no.11
• /
• pp.1423-1433
• /
• 2018

Recently, a permanent magnet synchronous motor of middle and small-capacity has high torque, high precision control and acceleration / deceleration characteristics. But existing control has several problems that include unpredictable disturbances and parameter changes in the high accuracy and rigidity control industry or nonlinear dynamic characteristics not considered in the driving part. In addition, in the drive method for the control of low-vibration and high-precision, the process of connecting the permanent magnet synchronous motor and the load may cause the response characteristic of the system to become very unstable, to cause vibration, and to overload the system. In order to solve these problems, various studies such as adaptive control, optimal control, robust control and artificial neural network have been actively conducted. In this paper, an incremental encoder of the permanent magnet synchronous motor is used to detect the position of the rotor. And the position of the detected rotor is used for low vibration and high precision position control. As the controller, we propose augmented state feedback control with a speed observer and first order deadbeat disturbance observer. The augmented state feedback controller performs control that the position of the rotor reaches the reference position quickly and precisely. The addition of the speed observer to this augmented state feedback controller compensates for the drop in speed response characteristics by using the previously calculated speed value for the control. The first order deadbeat disturbance observer performs control to reduce the vibration of the motor by compensating for the vibrating component or disturbance that the mechanism has. Since the deadbeat disturbance observer has a characteristic of being vulnerable to noise, it is supplemented by moving average filter method to reduce the influence of the noise. Thus, the new controller with the first order deadbeat disturbance observer can perform more robustness and precise the position control for the influence of large inertial load and natural frequency. The simulation stability and efficiency has been obtained through C language and Matlab Simulink. In addition, the experiment of actual 2.5[kW] permanent magnet synchronous motor was verified.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.13 no.5
• /
• pp.336-343
• /
• 2008

This paper proposes a novel sensorless control scheme for a Permanent Magnet Synchronous Motor (PMSM) by using a parallel reduced-order Extended Kalman Filter. The proposed scheme can obtain rotor position and speed by back-EKF that is estimated by reduced-order ETD and save computation time great)y due to using a parallel structure that works by turns every sampling time. Therefore, proposed scheme has merits of conventional EKF, and problems of parameter sensitivity are partially overcome. And proposed scheme can safely estimate rotor speed and position by using new algorithms according to driving regions. Experimental results show the validity of the proposed estimation technique, and to verify the merit of the proposed scheme, a comparison of a new reduced-order EKF algorithm with a conventional EKF algorithm has been also made in terms of computation time.

• Journal of Power Electronics
• /
• v.10 no.5
• /
• pp.548-554
• /
• 2010

In this paper, a 1.5 kW Interior Permanent Magnet Synchronous Generator (IPMSG) with a power conditioner for the grid integration of a variable-speed wind turbine is developed. The power-conditioning system consists of a series-type 12-pulse diode rectifier powered by a phase shifting transformer and then cascaded to a PWM voltage source inverter. The PWM inverter is utilized to supply sinusoidal currents to the utility line by controlling the active and reactive current components in the q-d rotating reference frame. While the q-axis active current of the PWM inverter is regulated to follow an optimized active current reference so as to track the maximum power of the wind turbine. The d-axis reactive current can be adjusted to control the reactive power and voltage. In order to track the maximum power of the wind turbine, the optimal active current reference is determined by using a simple MPPT algorithm which requires only three sensors. Moreover, the phase angle of the utility voltage is detected using a simple electronic circuit consisting of both a zero-crossing voltage detecting circuit and a counter circuit employed with a crystal oscillator. At the generator terminals, a passive filter is designed not only to decrease the harmonic voltages and currents observed at the terminals of the IPMSG but also to improve the generator efficiency. The laboratory results indicate that the losses in the IPMSG can be effectively reduced by setting a passive filter at the generator terminals.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.16 no.3
• /
• pp.266-273
• /
• 2011

This paper proposes a novel sensorless control scheme for a Permanent Magnet Synchronous Motor (PMSM) by using a parallel reduced-order Extended Kalman Filter. The proposed scheme can obtain rotor position and speed by back-EMF that is estimated by reduced-order EKF and save computation time greatly due to using a parallel structure that works by turns every sampling time. Therefore, proposed scheme has merits of conventional EKF, and problems of parameter sensitivity are partially overcome. And proposed scheme can safely estimate rotor speed and position by using new algorithms according to driving regions. Experimental results show the validity of the proposed estimation technique, and to verify the merit of the proposed scheme, a comparison of a new reduced-order EKF algorithm with a conventional EKF algorithm has been also made in terms of computation time.

• The Transactions of the Korean Institute of Electrical Engineers B
• /
• v.48 no.2
• /
• pp.63-68
• /
• 1999

This pper describes a digital sensorless drive of permanent magnet brushless DC motors. In order to detect in real time the rotor positions of which Emf becomes zero, terminal voltages are sampled during PWM duty cycle. This method generates detection error in indirect sensed position, which is the harmonic component of PWM frequency. In this paper, the drive adopted Butterworth low pass filter for rejection of the sensing error and for accurate estimation of commutation time. Analytical design process of the digital filter is proposed and the experimental results show that the performance of the proposed sensorless drive is superior to that of the sensorless drives without filterint.

• Proceedings of the KIPE Conference
• /
• 1999.07a
• /
• pp.1-3
• /
• 1999

The implementation of the compact gearless elevator system with Permanent Magnet Synchronous Motor is presented. For the purpose of the voltage suppression in the motor input side, the LRC filter is used. The automatic encoder alignment algorithm with rotor pole position is developed, and it is available in the full range of the load. The implemented system makes 11% energy savings comparing the system with the induction motor.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.1
• /
• pp.160-167
• /
• 2010

This paper proposes an adaptive sliding mode observer (SMO), which adds the estimation function of the stator resistance to a new sliding mode observer for the robust sensorless control of permanent magnet synchronous motor (PMSM) with variable parameters. To reduce the chattering problem commonly found in the conventional sliding mode observer where the low-pass filter and additional position compensation of the rotor are used, the sigmoid function is used for the control of a switching function in this research. With the estimation of the stator resistance, the proposed observer can improve the control performance by reducing the estimation error of the motor's speed. Note that the stator resistance is varying with the ambient temperature and becomes an error source for the sensorless control of PMSM. The new sliding mode observer has better efficiency than the conventional adaptive sliding mode observer by reducing the time consuming integral calculations. The stability of the proposed adaptive sliding mode observer is verified by the Lyapunov function in determining the observer gains, and the effectiveness of the observer is demonstrated by simulations and experiments.

• Journal of Power Electronics
• /
• v.8 no.4
• /
• pp.354-362
• /
• 2008

This paper presents neural load torque compensation method which is composed of a deadbeat load torque observer and gains compensation by a parameter estimator. As a result, the response of the PMSM (permanent magnet synchronous motor) obtains better precision position control. To reduce the noise effect, the post-filter is implemented by a MA (moving average) process. The parameter compensator with an RLSM (recursive least square method) parameter estimator is adopted to increase the performance of the load torque observer and main controller. The parameter estimator is combined with a high performance neural load torque observer to resolve problems. The neural network is trained in online phases and it is composed by a feed forward recall and error back-propagation training. During normal operation, the input-output response is sampled and the weighting value is trained multi-times by the error back-propagation method at each sample period to accommodate the possible variations in the parameters or load torque. As a result, the proposed control system has a robust and precise system against load torque and parameter variation. Stability and usefulness are verified by computer simulation and experiment.

• Journal of Electrical Engineering and Technology
• /
• v.9 no.5
• /
• pp.1614-1622
• /
• 2014

A novel equivalent flux sliding-mode observer (SMO) is proposed for dual three-phase interior permanent magnet synchronous motor (DT-IPMSM) drive system in this paper. The DT-IPMSM has two sets of Y-connected stator three-phase windings spatially shifted by 30 electrical degrees. In this method, the sensorless drive system employs a flux SMO with soft phase-locked loop method for rotor speed and position estimation, not only are low-pass filter and phase compensation module eliminated, but also estimation accuracy is improved. Meanwhile, to get the regulator parameters of current control, the inner current loop is realized using a decoupling and diagonal internal model control algorithm. Experiment results of 2MW-level DT-IPMSM drives system show that the proposed method has good dynamic and static performances.