Nowadays, switchedreluctance motors (SRM) attract more and more attention. The SRM is simple to construct. It has not only a salient pole stator with concentrated coils, but also a salient pole rotor without any conductors or magnets. Simplicity makes the SRM inexpensive and reliable, and together with its high speed capacity and high torque to inertia rotor ratio make it a superior choice in different applications. References [1-2] show the implementations of the control of the SRM is not an easy task. The motor’s double salient structure makes its magnetic characteristic highly nonlinear. Therefore, its mathematical model is too complex to be analytically developed. Since the 1960’s, with the advent of power electronics and high power semiconductor switches, control of the SRM become much easier and there has been a renewed interest in SRM drives .
Compared to (9), (21) reduces the maximum gain of the controller and brings oscillations.  Proposes a predictive current controller to solve the problem. While predictive current controller increases the calculation burden for DSP, especially for nonlinear systems such as SRMs.  recommends that current should be sampled at t(k−1/2), which means i(k) is estimated by
where the asterisk denotes the complex conjugate. Equation ( 8 ) demonstrates that electrons are rapidly heated due to the dissipation of the parallel electron current associated with localized SWDSA waves. The localization of the latter could be caused by the self-modulation [ 19, 27, 32 ] of SWDSA wave packets by quasi-stationary density ﬂ uctuations in the solar coronal magnetoplasma. On the other hand, the localization of nonlinear short wavelength drift-Alfvén waves in the form of two-dimensional vortices has been described using a nonlinear model involving kinetic ions and ﬂ uid electrons [ 33, 34 ] in an inhomogeneous magnetoplasma, with applications to the magnetopause of the Earth ’ s magnetosphere and to magnetically con ﬁ ned plasma. The effects of ion trapping in electron acoustic vortices [ 35, 36 ] also provides an alternative localization mechanism
The SwitchedReluctanceMotor (SRM) drives have recently gained considerable attention among researchers due to several reasons. In construction, the SRM is simplest of all electric machines. Only the stator has windings. The rotor contains no conductors or permanent magnets. It consists simply of steel laminations stacked onto a shaft. It is because of this simple mechanical construction that SRMS carry the promise of low cost, which in turn has motivated a large amount of research on SRMs in the last decade. The mechanical simplicity of the device, however, comes with some limitations. Like the brushless DC motor, SRMs cannot run directly from a DC bus or an AC line, but must always be electronically commutated. Also the saliency of the stator and rotor is necessary for the machine to produce reluctance torque, causes strong non-linear magnetic characteristics, complicating the analysis and control of the SRM. Not surprisingly, industry acceptance of SRMs has been slow. This is due to combination of perceived difficulties with the SRM, the lack of commercially available electronics with which to operate them, and the entrenchment of traditional AC and DC machines in the market place.
To avoid this problem, increasing the number of rotor and stator poles should be considered as one solution to the problem which will also minimize the torque ripples. Actually in order to involve four poles in the torque production mechanism; one need to have a 12 /8 motor, and when motor size is reduced, availability of space for windings becomes an issue. One method to solve this problem were presented by Afjei  through distributing the stator poles along the length of the motor by having different independent sections or phases where each phase has the same number of rotor and stator poles producing the MSRM. Actually, (MSRM) is the prime interest of most researchers to solve insufficient starting torque problem , .
Maged N. F. Nashed received his B.S. degree in Electrical Engineering, from Menoufia University, Egypt, in May 1983, his Diploma of Higher Studies from Cairo University, May 1990, his M.SC. degree in Electrical Engineering, from Ain Shams University, Cairo, Egypt, in April 1995 and his Ph.D. in Electrical Engineering, from Ain Shams University, Cairo, Egypt, in January 2001. He was a researcher for Fukuoka Institute of Technology, Japan, 2005. Since 1989, he has been a researcher with the Department of Power Electronic and Energy Conversion, Electronic Research Institute. From 2008 works as associate professor of power electronics in the same Institute. He is engaged in research on power electronics; drive circuit, control of drives and renewable energy.
brushless motor. The design of SR motor having torque, power, speed range and eﬃciency values competitive to those of PM motor has been investigated for hybrid electric vehicles in . Comparison studies for SR and PM motors have also been carried for electric bicycles  and electric brakes . However, the plausibility of replacing PM motor with SR motor for high temperature, space saving high torque density application is not reported and demands a thorough investigation of electromagnetic and thermal performances. This paper presents a performance comparison between SR motor and PM brushless motor considering the application speciﬁcations of ISI semi-automated vehicle. Preliminary design is carried out based on general rules of thumb and guidelines for design of high performance practical conﬁgurations . This design is then veriﬁed by Finite element analysis (FEA) which is considered to be an eﬀective tool for virtual prototyping of machine. Electromagnetic and thermal models are linked due to temperature dependent properties of materials including copper, lamination steel, magnets and coolant. Hence, a coupled electromagnetic thermal analysis of motor is carried out to estimate the temperature rise in diﬀerent parts of motor caused by electromagnetic losses. For simplicity and fast generation of results, thermal analysis is carried out using lumped parameter thermal model which is thermal counterpart of electric circuit analysis. A design of extended temperature, 12/8 inner rotor surface mounted permanent magnet motor is considered as the benchmark. The performance of each motor conﬁguration is compared in terms of output torque, losses, eﬃciency, weight, material cost and average temperature. In this paper application requirements and speciﬁcation of benchmark PM motor is described in Section 2. Section 3 describes the design process of SR motor and analysis using standard Finite Element Analysis (FEA) package. It also decribes the thermal modelling based on losses. A forced cooling system with nitrogen is proposed to increase lifetime of motors and to prevent the insulation breakdown. Section 4 describes the performance comparison of designed SR motor with benchmark PM motor. Final conclusions are drawn in Section 5.
linkage can be computed directly from terminal measurements: voltage and current of the phases and estimated flux linkage is obtained by the adaptive estimating algorithm. Actual and estimated flux linkages are used by a binary observer to estimate the velocity and rotor position. We must notice that all these processes are done online. The algorithm is tested on simulation of a real 6/4 motor that we manufactured and the relevant test results are presented. Although we did not actually construct the electronic drive to implement the proposed method experimentally as well, the validity of the simulation models for the electromotor under consideration has been extensively studied via both FE calculations and laboratory experimentation as reported in [24, 25] and its references. The method is suitable for velocity control applications, such as drill machines, washing machines and banknote counting machines.
Due to considerable non-linearity in the torque characteristics of SRM, the extensive requirement for lower torque ripple, good dynamic performance and cost sensitivity of the HEV traction application, most of the techniques discussed in the literature for this specific application are based on look-up table , . In , look- up tables were generated off-line by building an SRM model to profile the current for the flat torque waveform and stored in the controller. During on-line running, the controller searched the look-up tables for the current command. Another comprehensive controller to maximize efficiency and peak overload capability of SRM by using look-up tables for electric vehicle drives has been designed in . This controller has several look-up tables for different voltages. To calculate the control parameters for a certain torque- command/rotor-speed (operating point) and bus voltage, three interpolations have to be performed. As these interpolations are linear, they are subject to errors depending on the resolution of each table and the number of tables stored for different voltages. To overcome the above problem and also to reduce the table access time for interpolation, square tables are generated for each bus voltage. But still, there is a trade-off between the memory needed, execution time and the error rate. If the discretion steps of the rotor position and torque output are very small, the ideal current for minimizing the torque ripple will be found, but the amount of data will be enormous which needs a large memory and very long search time. On the other hand, if the discretion steps are big, the ideal current needed for reducing torque ripple may not be found. Unfortunately, at low speed, the torque ripple is sensitive to the current profile, and a slight deviation from the required profile may produce high torque ripple.
characteristics of the motor. Thus, if the motor characteristics changes with operating conditions, the controller tunings will also change to maintain the desired control performance. The tuning rules are implemented for obtaining the initial settings of the controller and this depends on the application .
Abstract —In this paper the simulink model for speed control of switch reluctancemotor is carried out using different speed controllers. The simulink model is designed for PI and Fuzzy logic controller separately and their result is compared. The speed controllers applied here are based on conventional PI controller and other one is Adaptive Neuro based Fuzzy logic controller. The PI controller is a special case of the PID controller in which the derivative of the error is not used. Fuzzy logic controller is an intelligent controller which uses fuzzy logic to process the input. In Industrial control FLC has various applications, Particularly where conventional control design techniques are difficult to apply. The ANFIS has theadvantages of expert knowledge of the fuzzy inference systemand the learning capability of neural networks. This controllerrealizes a good dynamic behavior of the motor, a perfect speedtracking with no overshoot and a good rejection of impact loadsdisturbance. The results of applying the adaptive neuro-fuzzycontroller to a SRM give better performance and highrobustness than those obtained by the application of aconventional controller (PI). The above controller was realizedusing MATLAB/Simulink. Index Terms— ANFIS, Torque Control, Switched ReluctanceMotor.
ABSTRACT -The SwitchedReluctanceMotor is a simple structure, ruggedness, and inexpensive manufacturing capability. The conventional power converter for SwitchedReluctanceMotor Drive requiring two switches per phase in this case study single switch is required per phase and its MATLAB simulation is done. This new drive system retain the unique feature of self starting for all rotor position. Simulation result based on non-linear model of the motor drive system, due to the single switch used cost of the drive is low and losses also minimized. This new drive system take attention due to its lowest cost structure ,packaging compactness, self-starting feature, variable-speed operation, fault tolerant tendency. Because of these merits, the new drive system offers a viable alternative for conventional drive. It is used in fan, blowers, hand tool, home appliances.
ABSTRACT: This paper describes the validation of Equivalent Circuit of SR Motor for dynamic analysis. This paper gives physical interpretation of Dynamic Equivalent Circuit. A mathematical model is presented for analysis of dynamics of SR Motor. Further, Validation of the proposed model is carried out with the help of experimentation on 4KW SR Motor. Finally obtained results are discussed using output waveforms of simulation as well as experimentation.
Abstract: This paper presents effective control characteristics to improve the performance of a tremendous effectual machine entitled Switchedreluctancemotor. Some of the controllers give better performance to get premeditated value; out of these controllers Model Predictive controller exhibit a good control strategy on power electronics devices. In this model predictive controller technique is employed in switchedreluctancemotor with a perfect switching converter. The main drawback of Switchedreluctancemotor is torque ripple and acoustic noise which are caused due to non linearity in winding current and electromagnetic property. The advantage of MPC is that it allows the easy inclusion of system constraints, thus different control objectives can be flexibly taken in account in different applications. Another remarkable merit of MPC is the inclusion of nonlinearities, such as harmonic spectrum control and switching frequency reduction. An effective IGBT controller is used as a switching circuit. By combing the characteristics of both the Model predictive controller algorithm and switching strategy of IGBT create a new effective control strategy technique for mitigating torque ripple and acoustic noise in switchedreluctancemotor.
Diagram of Fig 8 relates to the optimisation of radial proportions of the 4-phase linear switchedreluctance machine of the volume defined by the outside core diameter and length as in the prototype machine (80 and 106 mm) under excitation with phase currents of 'square' waveform having magnitude of 3.2 A. The geometry with mover diameter in the range between 38 and 40 mm, and slot diameter between 32 and 34 mm is capable of developing the thrust of around 155 N.
Abstract- This paper presents the modeling, simulation, and speed control aspects of a 3-phase 6/4 SwitchedReluctanceMotor (SRM) drives, using hybrid Artificial Intelligence Fuzzy Logic Controller system. Also a speed control design for SwitchedReluctanceMotor drive based on fuzzy logic controller is suggested. The fuzzy controller is proposed in this paper as speed controller for SRM. The whole control mechanism consists of a detailed report about the steady state and transient analysis of SwitchedReluctanceMotor. The control design results are then validated in real-time by Simulink / Matlab software package. The main aim of this project is to control the speed of the SwitchedReluctanceMotor very effectively using Fuzzy Logic Controller. Though PI controller is more popular and widely used, Fuzzy is something which is more advanced and efficient when compared to other conventional controllers.
change in the SRM configurations were done to improve its performance such as obtaining low torque-ripple or high torque density –. In some others, the motor topology is changed significantly. Segmented rotor SRMs and its different structures aiming at high torque intro- duced in , . The segmented rotor SRM also has a short-flux-path structure that may result in low loss ma- chine. Short-flux-path structures may be obtained by seg- mented stator SRM as well. Two-phase E-core SRMs and its different designs as in ,  show that the short- flux-path segmented stator design may reduce the iron material and losses. In some designs, the SRM topology is completely changed to obtain more torque and effi- ciency , . However, any major modification in SRM structure may affect on motor simplicity and costs. SRM has a low cost and rigid structure in comparison to the other motor types such as PM motors owing to the absence of any winding or magnetic materials on the rotor. On the other hand, SRM phases are normally driven with unipolar currents and then a variety of low cost power converter can be used. SRM also has comparable torque density among other motors particularly in low speeds. Beside these, SRM new technology may take advantages of some features such as short-flux-paths, flux-reversal- free stator and low copper usage that leads to the high ef- ficiency motor. All these features make it more appropriate for high power application such as EVs ,
SRM drives are attractive for use in many high performance industrial applications, with PWM used as an efficient means of power transfer, where high speed, torque and precision controls are required. In order to be able to run a SRM in high speeds some special considerations must be taken in drive circuit topology. One of those can be achieved by providing a path for faster discharge of current during the phase turn off time. This paper introduces three such topologies which serve such a purpose. In general, the essential features of the power switching circuit for each phase of reluctancemotor are comprised of two parts namely , a controlled switch to connect the voltage source to the coil windings to build up the current and the other part is an alternative path for the current to flow when the switch is turned off, since the trapped energy in the phase winding can be used in the other strokes. In addition, this protects the switch from the high current produced by the energy trapped in the phase winding.
The proposed switching technique for minimising the DC link capacitance has been implemented and tested. Fig. 10 shows the testing rig of the experimental SR motor drive system whose parameters are given in Table 1. The objective of the experiment is to verify that the proposed switching technique can be realized in a practical system for an effective reduction of the DC-link voltage ripple hence minimising the required DC-link capacitance when compared with the conventional hysteresis control. The motor is loaded in the experiment by an induction machine based dynamometer at its rated torque of 4 Nm.