PERMANENT MAGNETs (PM), which are one of the most vulnerable and important components of PERMANENT MAGNET MACHINEs, are at risk of deMAGNETization for reasons such as overheating and corrosion. One of the most critical tasks of engineers in the industry is to prevent the MACHINE's operation in the deMAGNETization condition and replace the MACHINE's defective PMs as much as possible. DeMAGNETization causes linkage flux reduction, electroMAGNETic force changes, and MACHINE heating. This paper presents a new approach for deMAGNETized PM diagnosis in a PERMANENT MAGNET linear SYNCHRONOUS MACHINE using wavelet packet transform. Due to the high sensitivity to the flux changes, the electromotive force signal was selected as a detection signal. By examining this method in different deMAGNETization cases, it is determined that this method has a proper performance. In this paper, the finite element software (Maxwell) and MATLAB were used to simulate the MACHINE and analyze the data, respectively.

Dc excitation of the field winding in a SYNCHRONOUS MACHINE can be provided by PERMANENT MAGNETs. PERMANENT MAGNET SYNCHRONOUS MACHINE (PMSM) can offer simpler construction, lower weight and size for the same performance, with reduced losses and higher efficiency. Thanks to the mentioned advantages these motors are widely used in different application, therefore analysis and modeling of them is very important. In this paper a new, fast and simple method is presented to study performance of a PMSM connected to the converter. For this purpose, average-value modeling and related analytical relations which leads to the desired characteristics such as electroMAGNETic torque, dc current and dc voltage is presented and applied to PMSM & converter system. The advantage of this model lies in reduction of computation time compares to the other dynamic models while keeping accuracy quite acceptable. This model is applicable for studying the steady-state performance of systems as well as dynamic performance.      

PERMANENT MAGNET SYNCHRONOUS MACHINEs (PMSM) are increasingly used because of their advantages over other MACHINEs, which include compactness, high efficiency, and well developed drives.. The substitution of the position sensors by advanced algorithms embedded in the controls hardware and software has been investigated for the last couple of decades. This Paper presents the modeling, analysis, design and experimental validation of a robust sensor less control method for PMSM based on Extended Kalman Filter. The position/speed sensor less control scheme along with the power electronic circuitry is modeled. The performance of the proposed control is assessed and verified for different types of dynamic and static torque loads.

In this paper, the sub-region method is used to analyze the outer-rotor PERMANENT MAGNET SYNCHRONOUS MACHINE. In this method, based on hypotheses such as geometry, electrical and MAGNETic characteristics, the MACHINE is divided into four sub-regions of groove, groove opening, air gap and MAGNET. Based on Maxwell's equations and considered assumptions, the governing partial differential equations for each sub-region are presented and solved analytically. In this paper, after calculating the air-gap flux density caused by the armature winding current and MAGNETs with three patterns of radial, parallel and Halbach MAGNETization, the other main quantities of the MACHINE are calculated accordingly. To validate the analytical model, the results obtained from MATLAB software are compared with the values obtained from the finite element method.

Background and Objectives: Designing a terminal sliding mode observer (TSMO) in order to estimate the potential faults in a wind turbine with a doubly fed induction generator (DFIG) has been studied in previous research works. In this paper, a method for fault detection of a PERMANENT MAGNET SYNCHRONOUS generator (PMSG) wind turbine using a TSMO is developed. Methods: The wind turbine (WT) dynamic model including, blades, drive train, 3kw PMSG, maximum power capture controller, and pitch controller is linearized around its equilibrium point and is simulated in MATLAB Simulink. A PID controller is designed for capturing the maximum power from wind. Also, a PI controller is designed in order to control the pitch angle. In this research, the blade imbalance fault (BIF), which is due to the difference between turbine blades’ mass distribution, is investigated. This fault may happen over time and causes rotor mass imbalance that leads to vibrations in the generator’ s shaft rotating speed. A fault detection system (FDS) is proposed using a terminal sliding mode observer in order to diagnose the BIF. Results: Using the designed TSMO, the estimation errors of not only measured states but also unmeasured states converge to zero in finite time. This leads to the fast action of the FDS before a failure happens. Using the proposed FDS, the states and fault are estimated such that the estimation errors of states and the fault converge to zero in 0. 033 seconds. Conclusion: The convergence of state estimation errors to zero in finite time, which is verified by simulation results, satisfies the authors’ expectation that using TSMO, the estimation errors of both output and non-output states converge to zero in finite time.

In this paper, a novel method to design and optimization of a 1.5 kW, 4-pole, 36-slot salient-pole PERMANENT MAGNET SYNCHRONOUS MACHINE (SPPMSM) based on a three-step skewed pole shoe method to reduce the output torque ripple and the cogging torque is investigated. In the first step, an initial model of the SPPMSM is designed, simulated, and verified through the Finite-Element method (FEM). The simulation results ensure the electroMAGNETic performance of the initial model of the MACHINE under any operating conditions. Next, a novel method to re-design and optimize the SPPMSM based on a three-step skewed pole shoe shape is presented.. The significant results obtained from the optimized model of the SPPMSM are as: The output average torque and the air gap flux density are increased approximately by 12.65% and 3.33%, respectively compared to the initial design of the SPPMSM. The torque ripple is an important parameter in the design of the MACHINE, and so, is decreased by about 16.03% which is equal to 10.41% in comparison with the initial model which is equal to 12.41%. The cogging torque in the initial model of the SPPMSM is equal to 0.036 N.m and with a 19.44% reduction, in the optimized model, it is 0.029 N.m. And finally, the back-EMF voltage of the SPPMSM is improved by 1.27% compared to the initial design model.