Jun-Young Song

A Novel Memetic Algorithm Using Modified Particle Swarm Optimization and Mesh Adaptive Direct Search for PMSM Design

In this paper, we propose a novel memetic algorithm, which is explorative particle swarm optimization (ePSO), combined with mesh adaptive direct search and apply it to the design of a permanent magnet synchronous machine (PMSM). The ePSO, which is modified from the PSO, drastically improves search time and iteration number at an exploration search stage. Unlike the existing methods, the proposed rule of start point selection takes an advantage of minimizing the search time. By applying the proposed algorithm to PMSM, we clarify the effectiveness of the proposed algorithm.

Analysis and Modeling of Concentrated Winding Variable Flux Memory Motor Using Magnetic Equivalent Circuit Method

In the preliminary design of the variable flux memory motor (VFMM), it is essential to examine the magnetization characteristics of the permanent magnet (PM) according to different direct-axis current pulses, which requires numerous parametric studies. In this paper, we propose a non-linear PM load-line model for concentrated winding surface-mounted PM VFMMs by making use of the magnetic equivalent circuit method, which is valid for investigating the PM magnetization state considering non-linear magnetic characteristics. The proposed method is validated through a comparison with the results of non-linear finite-element analysis.

Particle Swarm Optimization Algorithm With Intelligent Particle Number Control for Optimal Design of Electric Machines

In this study, we propose a modified particle swarm optimization (PSO) algorithm, which is an improved version of the conventional PSO algorithm. To improve the performance of the conventional PSO, a novel method is applied to intelligently control the number of particles. The novel method compares the cost value of the global best (gbest) in the current iteration to that of the gbest in the previous iteration. If there is a difference between the two cost values, the proposed algorithm operates in the exploration stage, maintaining the number of particles. However, when the difference in the cost values is smaller than the tolerance values assigned by the user, the proposed algorithm operates in the exploitation stage, reducing the number of particles. In addition, the algorithm eliminates the particle that is nearest to the best particle to ensure its randomness in terms of the Euclidean distance. The proposed algorithm is validated using five numerical test functions, whose number of function calls is reduced to some extent in comparison to conventional PSO. After the algorithm is validated, it is applied to the optimal design of an interior permanent magnet synchronous motor (IPMSM), aiming at minimizing the total harmonic distortion (THD) of the back electromotive force (back EMF). Considering the performance constraint, an optimal design is attained, which reduces back EMF THD and satisfies the back EMF amplitude. Finally, we build and test an experimental model. To validate the performance of the optimal design and optimization algorithm, a no-load test is conducted. Based on the experimental result, the effectiveness of the proposed algorithm on optimal design of an electric machine is validated.

Distance based intelligent particle swarm optimization for optimal design of permanent magnet synchronous machine

In this paper, we propose a novel particle swarm optimization (PSO), which is based on the Euclidian distance of particles. In the conventional PSO, the convergence speed is decreased, since several particles that are far from swarm does not converge but wander around search area. The proposed algorithm, which is named after distance based intelligent PSO, assigns a new position and velocity to the furthest particle. Therefore, all particles gather around global optimum, and it is able to search for global optimum faster than that of the conventional PSO. To validate effectiveness of the proposed algorithm, we compare it to the conventional PSO using three numerical test functions. In addition, interior permanent magnet synchronous motor (IPMSM), which has characteristic of magnetic saturation in magnetic steel sheet, is chosen as target model of optimal design. Total harmonic distortion of back-electromotive force is optimized by optimization of rotor topology. Through optimal design of IPMSM, effectiveness of the proposed algorithm for electric machine design is verified.

Computational Method of Effective Remanence Flux Density to Consider PM Overhang Effect for Spoke-Type PM Motor With 2-D Analysis Using Magnetic Energy

According to the conventional study, it is possible to perform 2-D finite-element analysis (FEA) to consider rotor overhang effect through the adjusted remanence flux density by employing an overhang parameter. The latest study addressed that the overhang parameter can be obtained using the variation of operating point of permanent magnet (PM). In this paper, we propose the novel computational method to calculate the effective remanence flux density directly to consider PM overhang effect making use of magnetic energy, which is applied for a spoke-type PM synchronous motor. The proposed method is validated through a comparison with the results of 3-D FEA.

Analysis and Modeling of Permanent Magnet Variable Flux Memory Motors Using Magnetic Equivalent Circuit Method

This paper presents an analytical method based on the magnetic equivalent circuit to derive permanent magnet (PM) load-lines of two general types of a variable flux memory motor (VFMM), which are circumferentially embedded (CE)-type and radially embedded (RE)-type PM motors. The proposed PM load-line models are valid and suitable for investigating the PM magnetization characteristics of VFMMs. It is validated via visible comparison with the PM load-lines derived by the finite-element method. Furthermore, by making use of the proposed method, the magnetization characteristics of several CE and RE VFMMs, which have different geometry parameters, have been examined and compared. According to the analysis results, RE-type VFMMs require approximately ten times larger remagnetizing field than CE-type VFMMs, although RE VFMMs are further influenced by demagnetizing field than CE VFMMs.

Phase Advance Control to Reduce Torque Ripple of Brush-less DC Motor According to Winding Connection, Wye and Delta

In this research, the characteristics of Brush-less DC (BLDC) motor in accordance with winding connection method, both Y-connection and D -connection, has been identified with design methodology simply. BLDC motor has been designed for both winding connections, and their torque analysis has been performed considering ideal current source analysis and voltage source analysis with 6-step control. In addition, to reduce torque ripple of BLDC motor, caused by coil inductance, on voltage source analysis with 6-step control, we have proposed suitable control method which is Phase Advance Control. It is verified that the torque ripple has been decreased by virtue of phase advance control, advancing and widening conduction angle of switching, via performance analysis by Finite Element Analysis.

Characteristics Analysis Method of Axial Flux Permanent Magnet Motor based on Two-Dimensional Finite Element Analysis

Three-dimensional (3-D) finite element analysis is generally required to analyze the performance of an axial flux permanent magnet (AFPM) motor because it has asymmetrical characteristics along the z-axis. Although the computing performance of CPU is enhanced owing to technological developement, a large amount of analysis time is required for 3-D finite element analysis (FEA). This paper presents a method of AFPM motor to an equivariant linear synchronous permanent magnet (ELSPM) motor, both of which have identical output performance. The output performance of the proposed ELSPM motor becomes identical to that of the AFPM under the mandatory condition that the PM magnetic energy of both the models must be identical. The validity of the proposed ELSPM motor in terms of the accuracy and computation time is verified by comparing its results with the results of the AFPM motor based on the FEA.

Distance-based Intelligent Particle Swarm Optimization for Optimal Design of Permanent Magnet Synchronous Machine

In this study, we propose a novel intelligent particle swarm optimization(PSO). In case of PSO, when particles approach to optimum point, particles roam near global optimum. Therefore, PSO takes unnecessary function call and long convergence time. In order to solve these problems, we propose distance based intelligent particle swarm optimization(DbIPSO). DbIPSO calculate distance of every particle and when distance is lower than assigned value, best particle absorbs near particles to reduce function call and convergence time. By applying proposed algorithm to optimal design of permanent magnet synchronous machine, we validate its effectiveness and performance.

Design of 100kW propulsion motor for electric conversion vehicle based on vehicle driving performance simulation

In this study, design of propulsion motor based on driving performance simulation analysis is carried out The analysis is implemented based on actual vehicle specifications, and values which satisfy target performances are chosen as parameters for motor. Based on this simulation, designing of 100kW motor for electric conversion vehicle is accomplished. In order to consider magnetic saturation characteristic, Finite Element Analysis(FEA) is used in designing interior permanent magnet synchronous motor(IPMSM). Using this specific motor designed, the driving performance simulation is again carried out to verify validation of the method.