In recent years, for ac-ac conversion system are widely applied for adjustable speed operation of electrical machines in various industries. This gives the high performance, efficiency and reduced costs of the system. It can also used for flywheel energy storage application, wind power generators and controlling mechanical variables -. Many industrial processors such as assembly lines must operate at different speeds for different products like flow from pump or fan. Basically for energy conversion system the back-to-back system is mostly used because of its simple structure. This back-to-back system consists of two voltage source inverters (VSIs), common dc-link capacitor and an input filter. But this system increases cost, complexity and losses. Instead of this system, the doubly fed induction machine (DFIM) is considered. The drive system with the simplified energy conversion system is shown in fig.1. This reduced the costs, the complexity and the energy conversion stages .
Woundrotorinduction generators (WRIGs) have a simple construction, are robust and can provide a stable supply when driven at varying speeds. Furthermore, WRIGs allow rotor resistance control which produces better output power over a wide range of wind conditions making it well-suited for application in wind turbines . A WRIG is also flexible in application as it can be operated as an isolated generator with capacitors to supply reactive power required by the generator and loads . For instance, in a grid-connected system, there may be a need for stand-alone operation arising from excessive power or stability problems in the system. Despite the relative robust nature of this machine, there are still a variety of faults that occur in practice. Recently, more attention is being given to research into WRIG condition monitoring methods. Abnormal behaviours of WRIGs under faulty conditions may cause excessive damage to the turbine and interconnected equipment, further resulting in production loss due to unscheduled repairs . The possibility to diagnose a wider variety of faults at an incipient level is an ongoing challenge. In general, preventive maintenance has two major components, that is, to detect and diagnose a fault using suitable techniques and then to eliminate the condition that is reducing the performance of the machine . The most common problems in inductionmachines are inter- turn faults on stator and rotor windings, broken rotor bars and end rings, static and dynamic air-gap irregularities, bowed shaft, bearings misalignment and mechanical imbalances .
The Motor Winding Kit offers a new approach to teaching construction techniques for electrical machines. Starting with basic components such as laminations, motor ends, and magnet wire, the Motor Winding Kit allows the assembly of a squirrel-cage induction motor, a wound-rotorinduction motor, a three-phase synchronous machine, and a split-phase capacitor-start motor. All parts necessary for assembly of the four machines are included in the kit. Two types of stator laminations are included for winding a three-phase stator and a single-phase stator.
current the energy is first stored in and then restored from the dc circuit until the dc current reaches its reference value, which causes the spikes in the supply current. Then, at about 150 ms the reference value of the rotor speed is changed from 0 to 1000 r/min and finally at about 600 ms the load torque is changed from 0 to nominal value (22 N m). The dc current reference value is calculated using in (11). Negative slopes of are filtered using time constant of 100 ms. The output of the speed controller is limited to. The results show that the operation of the drive is stable. Also, it can be concluded that the measured stator currents follow the stator current references closely and that the oscillations in the stator currents are low.
control. Rotor flux, back EMF and reactive power techniques are popular MRAS strategies which have received a lot of attention. However, Rotor Flux based Model Reference Adaptive System (RF-MRAS), first proposed by Schauder, is the most popular MRAS strategy and a lot of effort has been focused on improving the performance of this scheme. Conventional RF-MRAS schemes use PI controller as the adaptive mechanism for speed estimation. The reason is that the conventional PI controller is easy to implement either by hardware or by software, inexpensive cost, and no deep mathematical theory is necessary to understand how the conventional PI controller works. In spite of the major features of the conventional PI controller, it has some disadvantages such as the high peak overshoot and response will be sluggish when there is sudden load disturbance [8-13].
Fixed speed systems are the simplest and most widely used arrangement. They operate at constant (or nearly constant) speed [also called constant speed constant frequency (CSCF) mode of operation]. This implies that regardless of the prime mover speed, the angular speed of the rotor is fixed and determined by the frequency of supply grid and gear ratio This arrangement, in general, has simple and reliable construction of the electrical part while the mechanical parts are subject to higher stresses and additional safety factors need to be incorporated in the mechanical design. This arrangement can use induction generator (IG) and the woundrotor synchronous generator (SG) as the electric machine. But the squirrel cage induction generator has been the prevalent choice. The reasons for this popularity are mainly due to its simplicity, high efficiency and low maintenance requirements. To compensate for the reactive power consumption of the induction generator, a capacitor bank (normally stepwise controlled) is inserted in parallel with the generator in order to obtain about unity power factor. Further, to reduce the mechanical stress and to reduce the interaction between supply grid and turbine during connection and start-up of the turbine, a soft starter is used. The main advantage of this system is that it is a simple and reliable arrangement. However, capacitors need to be cutin or cutoff regularly to maintain power factor. This random switching gives rise to undesirable transients in the line currents and voltages. The fluctuations in prime mover speed are converted to torque pulsations, which cause mechanical stress. This causes breakdown of drive train and gear box. The power generated from this arrangement is sensitive to fluctuations in prime mover speed. To avoid this pitch control of rotor blades is required.
Transient stability enhancement of induction generator is one of the main issues in wind power generator. Fault or any of sudden disturbances on power system may cause rotor speed instability and voltage instability. This paper investigates for transient stability enhancement of induction generator after fault. For transient stability enhancement, the method used in which unique property of reversing the rotating flux of stator field is employed. In this method, after clearing fault for short time rotating field of stator is reversed results in opposition between stator rotating field and mechanical torque. It is nothing but changing operating mode from generating to plugging. This operation avoids rotor from further acceleration. Simulation result shows that proposed method is efficient for enhancing transient stability. Since in this method, no need of any external equipment, proposed method is more attractive than previous methods, from economic point of view.
ABSTRACT: This paper gives study of DFIG based wind turbine power generation system. The proposed system reliability connected to grid under fault conditions is demonstrated in MATLAB/Simulink software. A wound type rotor based induction generator and back-to-back IGBT based converter used for design of DFIG. The proposed system has capability of generating maximum energy under low speed wind conditions. The control system was designed for pitch angle control, wind turbine power, DC bus voltage, grid voltage and reactive power control.
The accurate model of a faulty machine is the first stage, which has a considerable impact on accurate fault detection. Hence as shown in Fig. 1 (b), the Finite Element Method is used for simulating the resolver due to its high accuracy. However, there are some considerations that should be considered in the finite element simulation of resolver, including excitation type, setting time step, and stop time of simulation, assigning mesh operations, and selecting the solver that is discussed in detail in . In this paper, Ansys-Electromagnetic Suit 17.1 software is used for simulations. The excitation winding is on the rotor and fed using a high-frequency sinusoidal voltage. The rotor is rotated in a constant speed, and the induced voltages on the signal windings that are located on the stator are given as presented in Fig. 2.
In which single phase induction motor speed control by using TRIAC and 555 timer. The complete control circuitry depends on only one parameter i.e., Voltage. We know that torque developed is proportional to square of the voltage. Thus the applied voltage to induction motor stator terminals is controlled by TRIAC and its gate pulses. When pulses to the gate are delayed then reduced voltage is applied to the induction motor stator terminals and thus as voltage and torques are proportional to each other, torque decrease and simultaneously speed of the motor gets reduced. The control circuitry consists of the following:
In case of the quasi-steady operational state, the implemented control (1) to (10) could be modeled by numerical methods in a very simple manner. The usage of a sinusoidal current fed numerical model covers the innermost layer of Fig. 4 sufficiently. Thereby, the rotor revolves in the numerical Finite Element simulation with constant default speed. Attention has to be given to the almost known spatial phase angle of the (d,q) rotor system and the space current distribution in the stator. A i sq current component produces
The VFT is essentially a continuously adjustable phase shifting transformer that can be operated at an adjustable phase angle. The VFT consists of following core components: a rotary transformer for power exchange, a drive motor to control the movement or speed of the rotor and to control the transfer of power. A drive motor is used to apply torque to the rotor of the rotary transformer and adjust the position of the rotor relative to the stator, thereby controlling the magnitude and direction of the power transmission through the VFT . The world's first VFT, was manufactured by GE, installed and commissioned in Hydro- Quebec's Langlois substation, where it is used to exchange power up to 100 MW between the asynchronous power grids of Quebec (Canada) and New York (USA) .
However, apart from a few notable textbooks ,  and pa- pers on issues related to rotor resonances, e.g., behavior of lam- inated stacks – and unsymmetrical shafts , little sys- tematic work has been carried out on this aspect in recent years. This paper describes the finite-element analysis (FEA) of the rotor of a permanent magnet brushless dc motor having a rated speed and power of 120 000 r/min and 1.25 kW, respectively, and investigates the influence of design parameters, such as the axial length, the shaft length and diameter, on the natural frequencies. FEA predictions, using the ANSYS FE package, are validated extensively by measurements from impulse force response tests, using a modal impulse force hammer, an ac- celerometer, and a dynamic signal analyzer, HP 35660A. While the addition of a stator will affect the resonance modes, due to the interaction of the rotor permanent magnets with the stator, this is neglected in order to simplify the study. However, this will not affect the general observations. The main focus in this paper is on the resonant modes that will be excited during normal op- eration. Primarily, this includes all modes below the operating speed of the motor (2 kHz), but it is appreciated that the com- mutation strategy may excite resonance modes above 2 kHz, al- though that is not considered within this paper. The paper also considers the influence of the bearings and various design pa- rameters on the motor performance.
was chosen as it is representative of the major torque ripple component for distributed winding machines. This idea was first introduced in , where the minimum number of rotor position simulations required to avoid significant aliasing of torque harmonics was also discussed. It was shown that five rotor positions equally spaced over the stator slot pitch and with a random offset applied by the MOGA can minimize the fundamental and third torque ripple harmonics with very quick computation. Three examples of torque ripple evaluation are shown in Fig. 4. The torque waveform in the figure does not refer to any of the final designs presented in the paper, and refers to a non-optimal machine with a high per unit ripple for better evidence of the impact of torque sampling on torque ripple evaluation. The introduction of the random offset (Figs. 4b and 4c) reduces the simulation time per design case at the cost of a more noisy functional evaluation. The same candidate machine design can be evaluated more optimistically (Fig. 4b) or more realistically (Fig. 4c) according to the value of the random offset. Using this technique, the evaluation of one candidate motor consists only of five time-stepped FEA simulations and takes 2.6s on a Intel Xeon E5-1620 workstation (4 cores, 3.60 GHz, 16 GB ram). This result also takes advantage of the use of multi-core parallel calculation. Parallel computing is possible thanks to the capability of executing multiple instances of FEMM 4.2  in parallel via the “parfor” Matlab  command, purposely made for parallel execution of loop iterations. Four to six candidates can be simulated on a standard multicore personal computer, resulting in a significant increase of simulation speed. Computational times are discussed in the following subsection.
The control of such a plant described by the Eq. 3 to Eq. 6 becomes complicated because of intricate coupling between all the control inputs. This problem can be overcome by the control of field oriented quantities which reduces the control of an ac induction motor to that of a separately excited compensated dc motor. The current space vectors are defined by vectorial combination of the phase currents of the stator and rotor respectively as:
In order to make several measurements with healthy and faulty squirrel-cage induction motors a modern laboratory test bench was set up. It consists of an electrical machine coupled with rope brake dynamometer. The speed of the motor is measured by digital tachometer. The Virtual Instrument (VIs) was built up with programming in LabVIEW 8.2. This VIs was used both for controlling the test measurements and data acquisition, and for the data processing. A data acquisition card and acquisition board ELVIS are used to acquire the current samples from the motor under load. In order to test the system in practical cases, several measurements were made, where the stator current of a machine with known number of broken rotor bars was read. Current measurements were performed for a healthy rotor and also for the same machine having different number of broken rotor bar. The rated data of the tested three-phase squirrel cage induction machine were: 0.5 kW, 415V, 1.05 A and 1380(FL) r/min. Tests were carried out for non-constant load with the healthy motor, and with similar motors having up to 12 broken rotor bars.
particles , or varying the PM direction . Although these can be solutions to extend the field weakening, this would not improve the power density or the structural capability of the machine. A way of improving the power density of PM machines for high speed applications while also maintaining the structural integrity is subject to investigation. The main objective of this paper is to present a novel concept for an Interior Permanent Magnet (IPM) machine to overcome the electromagnetic and structural constraints of the target application. The application requirements and the initial design are presented in section II. Section III presents the proposed solid rotor solution for an IPM machine. To improve structural integrity and minimize eddy current losses, three different rotor design approaches are considered, namely: a combination of both laminations and solid steel, segmented solid steel, and slitted solid steel. A tradeoff study is carried out in Section IV. Section V presents detailed structural analysis of an optimized machine to limit the localized stress acting on the rotor body. Herein a novel design approach is proposed to overcome the structural limitation while also compromising efficiency against the starting requirements. In section VI, an experiment is performed to show the eddy current minimization through the proposed slitted approach in comparison with a solid rotor body. The challenges and limitations involved in the design and methods to overcome such issues are discussed.
When compared with “hybrid rotor-PM with DC FEC machines” and conventional IPMSM , HEFSMs with PM, DC FEC and armature coil as active parts placed on the stator have a robust rotor structure as their advantage similar with switch reluctance machines (SRMs), simple and rugged rotor; easy cooling system for heat dissipation which makes it suitable to be applied in high current density condition, as well as variable flux capabilities from DC FEC.
Induction motors have several advantages compared to d.c motors: their low cost, robustness and reliability. Although, d.c machines have traditionally been used for high performance applications, the development of power electronics has contributed to the use of advanced control techniques that have made it possible to extend the use of inductionmachines in those applications [1, 2]. One of these techniques is the well known field oriented control. Traditionally, there have been two conventional methods which field oriented control is achieved by them: direct-field oriented control (DFOC) and indirect field oriented control (IFOC). Direct field oriented control requires explicit knowledge of the rotor field orientation. Indirect field oriented controller implements a closed-loop rotor flux controller and requires the angular position of the rotor flux which is calculated by integrating the angular speed . This can be computed using the rotor speed and the stator current measurement. Unfortunately, the calculation of the angular position of the rotor flux is very sensitive to errors in rotor resistance which varies with the temperature. If care is not taken to compensate for the change, the flux orientation is lost, resulting in coupling between the d- and q-axes variables which leads to the
DFIG characteristics are affected by its injected rotor voltage. By varying the amplitude and phase angle of the rotor injected voltage, the DFIG torque speed characteristics are shifted from the over-synchronous to sub-synchronous speed range to generate electricity and also increases the DFIG pushover torque, thereby improving the stability of operation. The simulated stator real power characteristics of the DFIG show that with increase in the rotor injected voltage, the DFIG real power characteristics shifts more in to the sub-synchronous speed range and the pushover power of the DFIG rises. The increase of Vq results in the expansion of the DFIG torque and real power characteristics for its generating mode, but at the same time increase the inductive reactive power demand from the grid. Whereas, the increase of voltage can not only expand DFIG torque and real power characteristics for its generating mode but also reduces the DFIG inductive power demand and may even change it to capacitive. For both motoring and generating modes, the DFIG sends additional real power through its rotor to the grid. Unlike the stator power, the characteristics of rotor power are mainly influenced by the rotor injected voltage. The simulated stator real power characteristics of the DFIG show that with increase in the rotor injected voltage, the DFIG real power characteristics shifts more in to the sub- synchronous speed range and the pushover power of the DFIG rises. DFIG with closed loop is shown in figure given below: