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YILDIZ, AHMET

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YILDIZ

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AHMET

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Now showing 1 - 6 of 6
  • Publication
    A comparative study on the optimal non-linear seat and suspension design for an electric vehicle using different population-based optimisation algorithms
    (Inderscience Enterprises, 2019-01-01) Yıldız, Ahmet; YILDIZ, AHMET; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Otomotiv Mühendisliği Bölümü.; 0000-0001-5434-4368; T-8076-2018; HSF-3939-2023
    This paper presents a comparative study on the optimal non-linear seat and suspension design for an in-wheel-motor driven electric car using half vehicle model (HVM) by integrating different population-based optimisation techniques. The vehicle and the human body models are used to determine the optimal values leading to better ride comfort by means of different optimisation methods, including the particle swarm optimisation (PSO), the differential evolution (DE), and the genetic algorithm (GA). Since the non-linear approach reflects more realistic vibration behaviour than the linear one, the seat and suspension springs are assumed to have cubic progressive characteristics in the mathematical model. An objective function is proposed according to the feasible ideal solution of the root-mean-square (RMS) values of the seat, vehicle, and head accelerations and the suspension deflections considering the constrained functions. The results demonstrate that overall vibration amplitudes are significantly reduced and different techniques can provide a better reduction in different cases.
  • Publication
    Parametric synthesis of two different trunk lid mechanisms for sedan vehicles using population-based optimisation algorithms
    (Pergamon-Elsevier Science, 2021-02-01) Yıldız, Ahmet; YILDIZ, AHMET; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Otomotiv Mühendisliği Bölümü.; 0000-0001-5434-4368; HSF-3939-2023; T-8076-2018
    This paper proposes a parametric synthesis of two different trunk lid mechanisms for sedan vehicles, incorporating three different population-based optimization techniques: Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and the Differential Evolution (DE). For this purpose, the kinematic equations of the mechanisms are derived and implemented in the quasi-static analysis to determine the necessary driving forces. The lengths and initial angles of four-bar linkage are optimized in order to minimize the sum of the differences between the target and calculated hand force values. The optimization results of the design variables and the performances of the optimization methods are presented. The outcomes indicate that the proposed design procedure is able to provide a trunk lid mechanism in which the target value of driving force in every moving angle is achieved. Furthermore, it is observed that the optimization techniques show different performances due to the fact that they provide better and faster optimal solutions than each other for different cases. The results of this paper are of utmost importance for the manufacturer to obtain an automated design process for the trunk lid mechanisms. (c) 2020 Elsevier Ltd. All rights reserved.
  • Publication
    Characterization of the torsional vibration behavior of circular and rectangular cross-sectional arc springs: Theory and experiments
    (Walter De Gruyter, 2021) Fidancıoğulları, Samet; Yıldız, Ahmet; YILDIZ, AHMET; 0000-0001-5434-4368; T-8076-2018; HSF-3939-2023
    This paper is about the theoretical and experimental characterizations of the torsional vibration behavior of circular and rectangular cross-sectional arc springs. Firstly, the dynamic behaviors of arc springs with different cross-sectional wire profiles designed for a dual mass flywheel are modeled by mathematical formulations. After that, experimental tests are performed to verify these models and it is observed that the stiffness characterizations are in good agreement with experimental results. Lastly, the masses of two different arc springs are compared by regarding the same vibration stiffness criteria and it is demonstrated that the rectangular wire provides an arc spring with a 9.44 vol.-% lighter structure. Thus, the outcomes of this paper can be good references for the manufacturer about the numerical and experimental characterization of dual mass flywheel springs, especially for rectangular wire arc springs.
  • Publication
    Joerot rotor dynamics toolbox based on complex transfer matrix method
    (Amer Soc Mechanical Engineers, 2023-01-01) Nis, Hüseyin Tarık; Yıldız, Ahmet; Kılıçaslan, Alican; Nis, Hüseyin Tarık; YILDIZ, AHMET; Bursa Uludağ Üniversitesi; 0000-0001-6490-6109; KPA-5824-2024; EGR-9277-2022
    The demand for high-speed and high-precision lightweight rotors increases with the need for high-performance industrial machines. To manufacture such precision rotors, engineers are pushed to perform more detailed design analyses using the science of rotor dynamics. However, commercial rotor dynamics software that performs these analyses has high prices. In addition, the closed source code prevents the researcher from developing subroutines to work with their test data. These limitations in commercial software prevent researchers from solving unique rotor dynamics problems. For this reason, researchers around the world have been developing their rotor dynamics software based on the Finite Element Method (FEM). In this study, an in-house-developed & open-source rotor dynamics toolbox named JoeRot is developed based on the Complex Transfer Matrix Method (CTMM). The proposed toolbox can perform analyses faster than the FEM and allows modeling and solving unique rotor dynamics problem such as unbalance response. Various analyses such as plotting the Campbell diagram, finding natural frequencies, determining mode shapes, determining the system frequency response due to unbalance, instability threshold analysis, and plotting a critical velocity map can be carried out on the designed toolbox. To investigate the accuracy of the JoeRot toolbox, a comparison is made between the analytical method and the finite element method. As a result of this comparison, it is observed that natural frequencies and deflection frequency response values were obtained under a 0.46% error rate and 22.75 times faster than other compared methods.
  • Publication
    Structural design optimization of the arc spring and dual-mass flywheel integrated with different optimization methods
    (Walter De Gruyter Gmbh, 2022-02-23) Yıldız, Ahmet; YILDIZ, AHMET; Yılmaz, Önder; Karabulut, Hüseyin; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Otomotiv Mühendisliği Bölümü.; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Makina Mühendisliği Bölümü.; 0000-0001-5434-4368; 0000-0002-2806-4781; 0000-0001-5625-7292; T-8076-2018; HSF-3939-2023; KHZ-8294-2024
    This paper is about the structural design optimization of the torsional arc spring and the dual-mass flywheel (DMF) using three different population-based optimization techniques: Particle swarm optimization (PSO), differential evolution (DE), and genetic algorithm (GA). For this purpose, the equations of the motions of the vehicle powertrain are derived and implemented into the dynamic analysis to minimize the vehicle torsional vibrations. The parameters and initial angles of the arc spring are optimized by considering the objective function that is the sum of the maximum acceleration amplitudes of the crankshaft vibrations. The results demonstrated that the proposed design procedure is able to provide a proper arc spring and DMF inertias to reduce the torsional vibration significantly. Moreover, it is indicated that the DE optimization techniques provide best performances than others. Finally, it is also shown that the natural frequencies can be reduced by the DMF and the optimization results are under the idling critical speed of the engine. The obtained results of this paper are of utmost importance for the arc spring manufacturer about the design process considering both DMF and spring parameters simultaneously to minimize torsional vibration of the vehicle powertrain.
  • Publication
    Optimal design of a five-bar planar manipulator and its controller by using different algorithms for minimum shaking forces and moments for the largest trajectory in a usable workspace
    (Mdpi, 2022-11-01) Kavala Şen, Deniz; Yıldız, Ahmet; Kopmaz, Osman; Kavala Şen, Deniz; YILDIZ, AHMET; KOPMAZ, OSMAN; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Makina Mühendisliği Bölümü.; 0000-0001-5434-4368; 0000-0002-2429-8927; T-8076-2018; FVJ-8195-2022; DAF-9103-2022
    In this paper, a structural design and controller optimization process for a five-bar planar manipulator are studied using three different population-based optimization techniques: particle swarm optimization, genetic algorithm, and differential evolution. First, the desired kinematic properties of the manipulator, such as the position, velocity, and acceleration of the endpoint, are determined using inverse kinematics. Then, an optimization problem is created to minimize the shaking force and moments, and the desired kinematic quantities are implemented as constraints. All the link properties of the manipulator are defined as design variables, and the optimization results are obtained. The results show that it is possible to significantly reduce the shaking force and moment significantly thanks to the optimal design parameters. Finally, the controller is optimized to find the best PID gains considering the forward kinematics of the manipulator. It is observed that the shaking force and shaking moment can be reduced by 99% and 54%, respectively, which has a very positive effect on the accuracy of the trajectory tracking. Moreover, the performances of the optimization methods are compared by using the same number of iterations in the calculations, and thus, it can be seen that the GA method achieves the best results compared to the others. Therefore, the results of this study are of utmost importance for a manufacturer, who wants to design a five-bar planar manipulator and its controller.