Browsing by Author "Hacan, Ahmet Furkan"

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    Design Optimization of an Outer Rotor PMSM for a Drive Cycle Using an Improved Mode Algorithm for a Lightweight Racing Vehicle
    (Institute of Electrical and Electronics Engineers Inc., 2020) Coşdu, Muhammed Muhsin; Hacan, Ahmet Furkan; Tekgun, Burak
    Hub motors are widely used for light-weight electric drives. The aim of this paper is to design a highly efficient out-runner permanent magnet synchronous motor (PMSM) for a specific drive cycle in order to use it in an electro mobile contest called the 'Efficiency Challenge'. A multiobjective differential evaluation (MODE) algorithm is used to obtain a variety of different design options. The MODE algorithm is altered to incur less computational cost and yield better-distributed results in a comparison with traditional MODE. The alteration is performed in five different aspects: Pareto Front, Selection Algorithm, Population Size, Scaling Factor, and Rectification. The objectives for differential evaluation optimization are minimizing the motor mass and maximizing efficiency for the target drive cycle. The voltage limit and the torque ripple are defined as constraints. The optimization algorithm is written in MATLAB and the finite element analysis (FEA) is conducted in ANSYS/Maxwell 2D. The modified MODE algorithm is optimized for the PMSM with 100 generations and 3282 candidate designs. A well-distributed Pareto optimal solution set is obtained, and a suitable design is selected to be manufactured. © 2022 Elsevier B.V., All rights reserved.
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    Design Optimization of an Outer Rotor Pmsm for a Drive Cycle Using an Improved Mode Algorithm for a Lightweight Racing Vehicle
    (IEEE, 2020) Cosdu, Muhammed Muhsin; Hacan, Ahmet Furkan; Tekgun, Burak
    Hub motors are widely used for light-weight electric drives. The aim of this paper is to design a highly efficient out-runner permanent magnet synchronous motor (PMSM) for a specific drive cycle in order to use it in an electro mobile contest called the "Efficiency Challenge". A multiobjective differential evaluation (MODE) algorithm is used to obtain a variety of different design options. The MODE algorithm is altered to incur less computational cost and yield better-distributed results in a comparison with traditional MODE. The alteration is performed in five different aspects: Pareto Front, Selection Algorithm, Population Size, Scaling Factor, and Rectification. The objectives for differential evaluation optimization are minimizing the motor mass and maximizing efficiency for the target drive cycle. The voltage limit and the torque ripple are defined as constraints. The optimization algorithm is written in MATLAB and the finite element analysis (FEA) is conducted in ANSYS/Maxwell 2D. The modified MODE algorithm is optimized for the PMSM with 100 generations and 3282 candidate designs. A well-distributed Pareto optimal solution set is obtained, and a suitable design is selected to be manufactured.