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Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395

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Subject: search.filters.subject.Automotive IndustryWoS Q: search.filters.wosQuartile.N/A

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  • Conference Object
    Investigation of Compressive Performance of 3D Printed Carbon Fiber Reinforced Plastics
    (Soc. for the Advancement of Material and Process Engineering Janie@sampe.org, 2018) Eroglu, Fatih; Yildirim, Afsin Talha; Yesilyurt, Ogulcan; Sas, Hatice Sinem; Çiftçi, Cihan
    The compressive performance of Carbon Fiber Reinforced Plastics (CFRP) is an extensive research area of crashworthy structures due to high Specific Energy Absorption (SEA) rates. However, the traditional composite manufacturing techniques are limiting the implementation of CFRP in crash components of automobile industry. These limitations can be minimized with 3D printing technology, which can be replaced with the traditional composite manufacturing techniques by providing flexibility especially in terms of geometric complexities. In this study, the compressive performance of 3D printed CFRP samples with square and circular cross-sections are examined with different thickness and fiber volume fraction values. SEA rates obtained from axial compressive tests are compared and compressive performance of 3D printed samples is optimized in terms of crashworthiness. © 2018 Elsevier B.V., All rights reserved.
  • Conference Object
    Citation - Scopus: 11
    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., 2020-10-05) 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.