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Discusses the 27 papers in ISEF 1999 Proceedings on the subject of electromagnetisms. States the groups of papers cover such subjects within the discipline as: induction machines; reluctance motors; PM motors; transformers and reactors; and special problems and applications. Debates all of these in great detail and itemizes each with greater in‐depth discussion of the various technical applications and areas. Concludes that the recommendations made should be adhered to.

This paper presents a novel multiobjective optimal design of three phase induction motor using simulated annealing (SA) technique for minimizing annual material cost and annual loss cost as two objectives.

The design problem of a three‐phase induction motor is presented as a nonlinear multicriterion optimization problem on the basis of minimizing the annual cost of the motor. The annual cost referred is the sum of the annual interest and depreciation of motor active material costs, annual cost of active power loss of the motor and the annual energy cost required to supply such power loss. A computer package is built which generates initial values of motor parameters and gives the optimal values of these parameters with more than one objective function and nonviolated constraints. The problem is solved by giving weights which reflect the priority of objective functions. The SA technique is used as a tool to solve the problem.

To verify the validity, the proposed method is applied to a three‐phase induction motor design. From the results, it is found that the proposed method is fast and efficient and hence it is useful for multiobjective design of an induction motor.

This method is particularly useful in satisfying the needs of motor producer and consumer by prioritizing their needs and finally arriving at a best compromise solution.

The purpose of this paper is to analyze the performance of a new direct torque control (DTC) strategy dedicated to four‐switch three‐phase inverter (FSTPI)‐fed induction motor drives with extended speed range.

The approach is based on the synthesis of a suitable vector selection table in order to reduce torque ripple. The performance analysis is carried out based on three criteria: the total harmonic distortion; the switching loss factor; and the quality factor.

It has been clearly shown that the introduced DTC strategy offers high performance during both transient and steady‐state operations of the FSTPI‐fed induction motor drive, which are almost the same as those yielded by the Takahashi DTC strategy implemented in the same motor fed by a conventional six‐switch three‐phase inverter (SSTPI).

The work should be extended by an experimental validation of the simulation results.

The established results open up crucial benefits from the point of view of cost‐effectiveness and volume‐compactness of induction motor drives especially in large‐scale industries such as the automotive, where electric and hybrid propulsion systems are currently regarded as an interesting alternative to substitute or to assist the thermal propulsion systems.

The paper presents the implementation of a dedicated DTC strategy in FSTPI‐fed induction motor drives with extended speed range. The proposed DTC strategy offers interesting performance compared with that yielded by the Takahashi DTC strategy implemented in the same motor fed by an SSTPI.

The aim of this research paper is to examine the bio‐inspired optimization algorithms, namely, genetic algorithm (GA), particle swarm optimization (PSO) and bacterial foraging optimization (BFO) algorithm with adaptive chemotactic step for determining the steady‐state equivalent circuit parameters of the three‐phase induction motor using a set of manufacturer data.

The induction motor parameter determination issue is devised as a nonlinear constrained optimization problem. The nonlinear equations of various quantities (torque, current and power factor) are derived in terms of equivalent circuit parameters from a single and a double‐cage model, and then, equates to the corresponding manufacturer data. These equations are solved by the bio‐inspired algorithms. Using the squared error between the determined and the manufacturer data as the objective function, the parameter determination problem is transferred into an optimization process where the model parameters are determined that minimize the defined objective function. The objective function is iteratively minimized using GA, PSO and BFO techniques. In order to balance the exploration and exploitation searches of the BFO algorithm, an adaptive chemotactic step is utilized.

Comparisons of the results of GA, PSO, BFO and IEEE Std. 112‐F (using no‐load, locked‐rotor and stator resistance tests) methods for two sample motors are presented. Results show the superiority of the bio‐inspired optimization algorithms over the classical one. Besides, BFO‐based parameter determination method is observed to obtain better quality solutions quickly than GA and PSO methods.

The parameters obtained by the proposed approaches can be used in analyzing the stalling and/or reacceleration process of a loaded motor following a fault or during voltage sag condition as well as in system‐level studies.

The most significant contribution of the research is the potential to determine the equivalent circuit parameters of induction motor only from its manufacturer data without conducting any lab tests on the motor. The bio‐inspired optimization based parameter determination approaches are faster and less intrusive than the IEEE Std. 112‐F method.

The purpose of this paper is to present a comparative study of the various soft computing techniques and their application to optimum design of three‐phase induction motor design.

The need for energy conservation is increasing the requirements for increased efficiency levels of induction motor. It is therefore important to optimize the efficiency of induction motor in order to obtain significant energy savings. To optimize the efficiency, design of the induction motor has to be chosen appropriately. In this paper, computational intelligence techniques such as artificial neural network, fuzzy logic, genetic algorithm, differential evolution, evolutionary programming, particle swarm optimization, simulated annealing approach, radial basis function, and hybrid approach are applied to solve the induction motor design optimization problem.

These methods are tested on two sample motors and the results are compared and validated against the conventional Modified Hooke‐Jeeves design results and the effectiveness of each proposed method has also been illustrated in detail.

This comparison will be highly useful for the design engineers in selecting the best method for obtaining the optimal dimensions of three‐phase induction motor.

Applies the field/circuit two‐dimensional method and improved circuit method to engineering designs of the induction motor with stator cores made of amorphous iron. Exploiting of these methods makes possible computation of many different specific parameters and working curves in steady states for the “high efficiency” three‐phase small induction motor. Compares the results of this calculation with the results obtained for the classical induction motor with identical geometric structure.

The purpose of this paper is to study the development of novel multiphase induction motor (MPIM) with copper die cast rotor in the drive system of electric propulsion vehicles (EPV). It is estimated that the manufacturers are concerned about high torque,Efficiency, motor life, energy conservation and high thermal tolerance. To ensure maximum torque and efficiency with multiphase winding and copper die cast technology to increasing high thermal tolerance, life, energy conversations. On other hand, it is very important of EPV application.

The focus of the investigation is threefold: the modified method carried out on MPIM both stator and rotor can overcome the current scenario problem facing by electric vehicles manufacture and developed perfect suitable electric motor for EPV applications. The design and simulation carried out finite element method (FEM) that was more accurate calculations. Finally developed prototype model of MPIM with copper die cast are discussed with conventional three phase Die casting Induction motor.

The paper confirmed the multiphase copper die-cast rotor induction motor (MDCrIM) is providing better performance than conventional motor. Proposed motor can bring additional advantage like heat tolerances, long life and energy conversations.

The experiments confirmed the MDCIM suitable for EPV Applications. The modified MDCIM of both stator and rotor are giving better result and good performance compared to conventional method.

The purpose of this paper is to present a comparative study of the thermal behavior and efficiency of an induction motor fed by a fault-tolerant Three-Level Neutral Point Clamped (3LNPC) inverter, under normal conditions as well as after a post-fault reconfiguration, following an open-circuit fault in the inverter. For this purpose, a Matlab/Simulink model and three-phase induction motor models using a finite element method (FEM) software were developed. Besides, some experimental tests were conducted for different values of the induction motor load torque and speed reference to validate the models.

To assess the thermal behavior and efficiency of the motor, electromagnetic and thermal models using a FEM software were developed. The coupling with the inverter drive is accomplished through a developed model in Matlab/Simulink which also includes the control system. The simulation tests were performed for a healthy and faulty inverter at different operating points of the three-phase induction motor. To validate the FEM models some experimental tests were performed.

When the inverter operates in reconfigured mode the motor losses are higher and consequently temperature is higher and the motor efficiency is lower. The developed models are an alternative to a more detailed study of the motor when fed by a 3LNPC inverter and consequent optimization of the control system.

With the developed tools, a better understanding of the motor behavior and performance is gained, allowing to forecast scenarios and optimize fault-tolerant control strategies for the drive.

The purpose of this paper is to present the application of an adaptive bacterial foraging (BF) algorithm for the design optimization of an energy efficient induction motor.

The induction motor design problem is formulated as a mixed integer nonlinear optimization problem. A set of nine independent variables is selected, and to make the machine feasible and practically acceptable, six constraints are imposed on the design. Two different objective functions are considered, namely, the annual active material cost, and the sum of the annual active material cost, annual cost of the active power loss of the motor and annual energy cost required to supply such power loss. A new adaptive BF algorithm is used for solving the optimization problem. A generic penalty function method, which does not require any penalty coefficient, is employed for constraint handling.

The adaptive BF algorithm is validated for two sample motors and benchmarked with the genetic algorithm, particle swarm optimization, simple BF algorithm, and conventional design methods. The results show that the proposed algorithm outperforms the other methods in both the solution quality and convergence rate. The annual cost of the induction motor is remarkably reduced when designed on the basis of minimizing its annual total cost, instead of minimizing its material cost only.

To the best of the knowledge, none of the existing work has applied the BF algorithms for electrical machine design problems. Therefore, the solution to this problem constitutes the main contribution of the paper. According to the huge number of induction motors operating all over the world, the BF techniques used in their design, on minimum annual cost basis, will lead to a tremendous saving in global energy consumption.

The purpose of this paper is to propose an analytical method for prediction of self‐sustained oscillations that might happen during low‐cost induction motor drive application. This forecast is needed to avoid unwanted oscillations that can be encountered for in fan, compressor and pump drives utilizing open‐loop frequency‐controlled three‐phase induction motor drives.

The paper presents the model of the induction motor drive system that includes inverter switches dead‐time and allows discontinuous current of front‐end rectifier. Stability analysis of proposed model was performed by tracing the eigenvalues of the overall system matrix.

Discontinuous rectifier current at light loads and the dead‐time of the inverter switches are the main sources of undesired low‐frequency self‐sustained speed oscillations in open‐loop controlled induction motor drives. The evaluated risk prediction is a function of drive and motor parameters and load level.

The proposed induction motor drive system model highlights the direct connection between the self‐sustained speed oscillations and the system parameters like inverter dead time, dc capacitor values, motor parameters and motor load level. Good accuracy of instability prediction is verified by dynamic simulation and by extensive experimentation.