• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.4B no.4
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• pp.184-189
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• 2004

In this paper, multi-object optimization based on a progressive quadratic response surface method (PQRSM) and a time stepping finite element method (FEM) is proposed. The new PQRSM and FEM are able to decide optimal geometric and electric variables of the switched reluctance motor (SRM) with two objective functions: torque ripple minimization and average torque maximization. The result of the optimum design for SRM demonstrates improved performance of the motor and enhanced relationship between torque ripple and average torque.

• Journal of the Korean Society of Industry Convergence
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• v.17 no.3
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• pp.113-121
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• 2014

This paper presents a optimization design of 10[W] single phase BLDC motor applied Notch shape. Cogging Torque causes noise, vibration and torque ripple so notched stator is proposed in this paper. Firstly, a single phase BLDC motor needs applying aymmetric air-gap shape because this type motor cannot help having dead-point which is zero torque position. However, using asymmetric air-gap structure causes cogging torque increase. Therefore, this paper proposes the notch shape structure. Notch shape structure has some advantages; low cost, easy to apply. There are 4 optimal factors selected in optimization process, which are position and size of notches. Through building a prototype, the result of FE analysis and the experimental measurement value are compared each other and then vailidity and utility of simulation will be verified.

• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1577-1581
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• 2014

This paper presents a method to minimize torque ripple of a V-type IPMSM using the PSO (Particle Swarm Optimization) method with FEM. The proposed algorithm includes one objective function and three design variables for a notch on the surface of a rotor. The simulation model of the V-type IPMSM has 3-phases, 8-poles and 48 slots with 2 notches on the one-pole rotor surface. The arc-angle, length and width of the notch are optimized to minimize the torque ripple of the motor. The cogging torque of the model is reduced by 55.6% and the torque ripple is decreased by 15.5 %. Also, the efficiency of the motor is increased by 15.5 %.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.227-242
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• 2015

This paper proposes a weighting factor optimization method in predictive control algorithm for torque ripple reduction in an induction motor fed by an indirect matrix converter (IMC). In this paper, the torque ripple behavior is analyzed to validate the proposed weighting factor optimization method in the predictive control platform and shows the effectiveness of the system. Therefore, an optimization method is adopted here to calculate the optimum weighting factor corresponds to minimum torque ripple and is compared with the results of conventional weighting factor based predictive control algorithm. The predictive control algorithm selects the optimum switching state that minimizes a cost function based on optimized weighting factor to actuate the indirect matrix converter. The conventional and introduced weighting factor optimization method in predictive control algorithm are validated through simulations and experimental validation in DS1104 R&D controller platform and show the potential control, tracking of variables with their respective references and consequently reduces the torque ripple.

• Journal of Electrical Engineering and Technology
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• v.10 no.2
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• pp.551-559
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• 2015

This paper's focus is in reducing the torque ripple and increasing the average torque by optimizing switching angles of 8/6 switched reluctance motor while implementing a robust speed controller in the outer loop. The mathematical model of the machine is developed and it is simulated using MATLAB/Simulink. An objective function and constraints are formulated and Optimum turn-on and turn-off angles are determined using Particle swarm optimization and Genetic Algorithm techniques. The novelty of this paper lies in implementing sliding mode speed controller with optimized angles. The results from both the optimization techniques are then compared with initial angles with one of them clearly being the better option. Speed response is compared with PID controller.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.188-194
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• 2015

This paper proposes a generalized regression neural network (GRNN) based algorithm for data interpolation and design optimization of brushless dc (BLDC) motor. The procedure makes use of magnet length, stator slot opening and air gap length as design variables. Cogging torque and average torque are treated as performance indices. The optimal design necessitates mitigating the cogging torque and maximizing the average torque by varying design variables. The data set for interpolation and ensuing design optimisation using GRNN is obtained by modeling a standard BLDC motor using finite element analysis (FEA) tool MagNet 7.1.1. The performance indices of the standard motor obtained using FEA are validated with an experimental model and an analytical method. The optimal design is authenticated using particle swarm optimization (PSO) algorithm and the performance indices of the optimal design obtained using GRNN is validated using FEA. The results indicate the suitability of GRNN as an interpolation and design optimization tool for a BLDC motor.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.49 no.10
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• pp.659-664
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• 2000

This paper presents a new design method for improving the torque performance of a switched reluctance motor (SRM) for high speed applications. The drawback of the conventional design method based on the overall static average torque maximization is that the torque control performance is degraded at high speed. On the other hand, the proposed method optimizes the torque profile by diving it into several regions so that it is suitable for high speed operation. This multi-objective optimization problem is solved by using a fuzzy optimization algorithm which incorporates a finite element method. The torque performance of the motor for various speed ranges is investigated and the optimally designed motor show a better performance at high speed.

• Journal of Magnetics
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• v.21 no.4
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• pp.570-576
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• 2016

The shape optimization of the stator and the rotor is important for electrical motor design. Among many motor design parameters, the stator tooth and yoke width are a few of the determinants of noload back-EMF and load torque. In this study, we proposed an equivalent magnetic circuit of motor stator for efficient stator tooth and yoke width shape optimization. Using the proposed equivalent magnetic circuit, we found the optimal tooth and yoke width for minimal magnetic resistance. To verify if load torque is truly maximized for the optimal tooth and yoke width indicated by the proposed method, we performed finite element analysis (FEA) to calculate load torque for different tooth and yoke widths. From the study, we confirmed reliability and usability of the proposed equivalent magnetic circuit.

• Journal of computational fluids engineering
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• v.19 no.3
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• pp.29-36
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• 2014

In the present study, an aerodynamic design optimization of UAV rotor blades was conducted using a genetic algorithm(GA) coupled with computational fluid dynamics(CFD). To reduce computational cost in making databases, a function approximation was applied using artificial neural networks(ANN) based on a radial basis function network. Three dimensional Reynolds-Averaged Navier-Stokes(RANS) solver was used to solve the flow around UAV rotor blades. Design directions were specified to maximize thrust coefficient maintaining torque coefficient and minimize torque coefficient maintaining thrust coefficient. Design variables such as twist angle, thickness and chord length were adopted to perform a planform optimization. As a result of an optimization regarding to maximizing thrust coefficient, thrust coefficient was increased about 4.5% than base configuration. In case of an optimization minimizing torque coefficient, torque coefficient was decreased about 7.4% comparing with base configuration.

• Journal of the Korea Institute of Military Science and Technology
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• v.3 no.2
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• pp.42-52
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• 2000

A torque control method of a switched reluctance motor for the position control of a tank gun is presented. One of the widely used torque control scheme, torque sharing function method, is investigated and a new torque sharing function method is proposed that extends the definition region of the conventional TSF to both the positive and negative torque production regions. By using this definition, all kinds of the control inputs that consider switching on/off angle control as well as the current profiling can be described. A parametrized representation of the current profiles is proposed by using a series of B-spline functions, which reduces memory requirement and enables additional controllers. Optimal determination of the TSFs are also investigated for various control objectives. Moreover, the comparison study of each objective is presented. Since this method generalizes all of the possible control input, the current and torque profiles obtained from the optimization are the most suitable control input that satisfy the objectives.