Jun-Young Song
Sungkyunkwan University
16 Papers
60 Citations
Jun-Young Song is an academic researcher from Sungkyunkwan University. The author has contributed to research in topics: Multi-swarm optimization & Magnetic flux. The author has an hindex of 7, co-authored 15 publications.
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Papers
Particle Swarm Optimization Algorithm With Intelligent Particle Number Control for Optimal Design of Electric Machines
TL;DR: A modified particle swarm optimization (PSO) algorithm is proposed, which is an improved version of the conventional PSO algorithm, aiming at minimizing the total harmonic distortion of the back electromotive force (back EMF).
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A Novel Memetic Algorithm Using Modified Particle Swarm Optimization and Mesh Adaptive Direct Search for PMSM Design
TL;DR: 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).
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Distance-based Intelligent Particle Swarm Optimization for Optimal Design of Permanent Magnet Synchronous Machine
TL;DR: Proposed distance based intelligent particle swarm optimization (DbIPSO) is applied to optimal design of permanent magnet synchronous machine and its effectiveness and performance are validated.
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Computational Method of Effective Remanence Flux Density to Consider PM Overhang Effect for Spoke-Type PM Motor With 2-D Analysis Using Magnetic Energy
TL;DR: In this paper, the authors proposed a 2D finite element analysis (FEA) 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.
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Characteristics Analysis Method of Axial Flux Permanent Magnet Motor based on Two-Dimensional Finite Element Analysis
TL;DR: In this paper, the authors presented a method of axial flux permanent magnet (AFPM) motor to an equivariant linear synchronous permanent magnet motor (ELSPM) with identical output performance.
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