Hyun-Kyo Jung

Shape optimization of electromagnetic devices using immune algorithm

A new method employing the immune algorithm (IA) as the search method for the shape optimization of an electromagnetic device is presented. The method is applied to the shape optimization of a pole face of an electromagnet. For the magnetic field analysis the finite element method is used. It is shown that the proposed method with the IA is very useful for the shape optimization of electromagnetic devices.

Multimodal function optimization based on particle swarm optimization

In this paper, a new algorithm for the multimodal function optimization is proposed, based on the particle swarm optimization (PSO). A new method, named the multigrouped particle swarm optimization (MGPSO), keeps basic concepts of the PSO, and, thus, shows a more straightforward convergence compared to conventional hybrid type approaches. Moreover, the MGPSO has a unique advantage in that one can search N superior peaks of a multimodal function when the number of groups is N. The usefulness of the proposed algorithm was verified by the application to various case studies, including a practical electromagnetic optimization problem

A study on comparison of optimization performances between immune algorithm and other heuristic algorithms

Usefulness of heuristic algorithms as the search method for diverse optimization problems is examined. Immune algorithm (IA), genetic algorithm (GA) and evolution strategy (ES) are used to search the optimal value for some numerical functions. Then those results are compared each other. It is shown that IA is more useful for most of problems. Especially the structure and characteristic of immune algorithm (IA) are inspected in detail. Finally a surface permanent magnet synchronous motor (SPMSM) is designed by using the algorithms.

Hybrid genetic algorithm for electromagnetic topology optimization

This paper proposes a hybrid genetic algorithm (GA) for electromagnetic topology optimization. A two-dimensional (2-D) encoding technique, which considers the geometrical topology, is first applied to electromagnetics. Then, a 2-D geographic crossover is used as the crossover operator. A novel local optimization algorithm, called the on/off sensitivity method, hybridized with the 2-D encoded GA, improves the convergence characteristics. The algorithm was verified by applying it to various case studies, and the results are presented herein.

Magnetic field analysis of 2-D permanent magnet array for planar motor

A new permanent magnet array for planar motor is proposed. The flux density distribution for the array is solved analytically by using the scalar magnetic potential equation. It is verified that the performance of the new magnet array is superior to the existing magnet arrays presented in patents.

Efficiency optimization of interior permanent magnet synchronous motor using genetic algorithms

This paper presents an optimal design method to maximize the efficiency of the interior permanent magnet synchronous motor. To do this, the efficiency of the motor is taken as the objective function, and the genetic algorithm is used as the optimization algorithm to find the optimal design variables of the objective function. To make a more accurate prediction of performance possible, the air gap flux density and d, q axis inductances obtained by an analytical method are compensated by using the results from FEM studies.

Niching genetic algorithm with restricted competition selection for multimodal function optimization

The niching method enables the genetic algorithm to be applied to the problems that require the location of multiple solutions in the search space. In this paper, a new niching method using restricted competition selection (RCS) is proposed to identify and search multiple niches (peaks) efficiently in a multimodal domain. To verify its validity, the proposed method is applied to some traditional mathematical problems and an induction motor design.

Optimal design of synchronous motor with parameter correction using immune algorithm

This paper presents a new technique for the optimal design of the surface permanent magnet synchronous motor (SPMSM) considering the parameter correction of synchronous reactance. The parameter correction for the design of SPMSM is performed by using the finite element method (FEM). The armature resistance and the residual flux density of rotor magnet are corrected through the thermal analysis. The advanced immune algorithm (AIA) is used in the optimization procedure.

Induction motor design for electric vehicle using a niching genetic algorithm

In the case of the shape or structural optimization of induction motor design, it is necessary to identify multiple optimal profiles by locating local optima as well as global. Niching methods extend genetic algorithms to domains that require the location and maintenance of multiple solutions. In this paper, optimal design of an induction motor for an electric vehicle using a niching method adopting restricted competition selection is proposed. The evaluation criteria and the standards of the best design selection are also presented.

Optimal core shape design for cogging torque reduction of brushless DC motor using genetic algorithm

The cogging torque in the small brushless DC (BLDC) motors used in the digital versatile disk (DVD) driving system or hard disk drive (HDD) system can cause some serious vibration problems. In this paper, some core shapes that reduce cogging torque are found by using the reluctance network method (RNM) for magnetic field analysis and genetic algorithms (GAs) for optimization. The outer rotor type BLDC motor for the DVD ROM driving system is optimized as a sample model.