Person: ERDAL, HASAN
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ERDAL
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HASAN
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Publication Metadata only Designing a Hardware and Software for the Performance Evaluation of Combustion Engine Equipped with Mechatronics System(2005-01-01) ERDAL, HASAN; Yurdagul E., ERDAL H., Baba F.In this study, a hardware and software system were designed to measure and evaluate the performance of a 1.6 16 V Ford Zetec motor. The factors effecting motor performance such as amount and temperature of air taken into the cylinders, temperature of the cooling liquid, data of motor cycle and upper dead point, opening time of the valves, state of gas regulator and quantity of the oxygen in exhaust were measured and computerized. In order to determine the operational characteristics of these sensors a series of experiments were carried out. A software was developed by delphi programming in order to register and display the data coming from the sensors.Publication Metadata only Controlling of grid connected photovoltaic lighting system with fuzzy logic(PERGAMON-ELSEVIER SCIENCE LTD, 2010) ERDAL, HASAN; Saglam, Safak; Ekren, Nami; Erdal, HasanIn this study, DC electrical energy produced by photovoltaic panels is converted to AC electrical energy and an indoor area is illuminated using this energy. System is controlled by fuzzy logic algorithm controller designed with 16 rules. Energy is supplied from accumulator which is charged by photovoltaic panels if its energy would be sufficient otherwise it is supplied from grid. During the 1-week usage period at the semester time, 1.968 kWh energy is used from grid but designed system used 0.542 kWh energy from photovoltaic panels at the experiments. Energy saving is determined by calculations and measurements for one education year period (9 months) 70.848 kWh. (C) 2009 Elsevier Ltd. All rights reserved.Publication Metadata only MATLAB / Simulink tabanlı otomatik kod üretimi ve gömülü anti-windup PI denetleyici tasarımı(2014-09-11) ERDAL, HASAN; SAYIN, FATİH SERDAR; ERDAL H., SAYIN F. S.Publication Metadata only Industry 4.0 and engineering education: The case of modular production dystem(2020-12-30) ERDAL, HASAN; TAŞKIN S., TUNÇALP B. K., ERDAL H.Publication Metadata only Development of a driving cycle for Istanbul bus rapid transit based on real-world data using stratified sampling method(PERGAMON-ELSEVIER SCIENCE LTD, 2019) ERDAL, HASAN; Kaymaz, Habib; Korkmaz, Hayriye; Erdal, HasanEnvironmental as well as financial issues forces to develop clean, efficient, and sustainable vehicles which constitutes an integral part of our daily life for urban transportation. Nevertheless, exhaust emissions of conventional internal combustion engine vehicles are the major source of global warming lead greenhouse effect. One solution for this issue is hybridization/electrification of the vehicles. One of the most important tools which can help to test performances of technical solutions systematically is driving cycles representing real driving conditions for vehicle emissions testing and estimation. When the history of the driving cycles was reviewed, it can be seen that there were big changes from constructing synthetically to real world cycles and from emission-focused cycles to emission, pollution and fuel consumption focused cycles. And now, a new application such as hybridization and/or electrification has been added to driving cycles. Main aim of this study is to create a practical driving cycle for Bus Rapid Transit (BRT) vehicles. To do this, characteristic driving parameters such as speed, distance, time, acceleration have been determined first. Data acquisition from conventional vehicles running on Istanbul route was performed and then data were analysed. A driving cycle was developed by using Proportional Stratified Sampling (PSS) technique. Comparison between constructed driving cycle and the real-world data show that difference is less than 10%. And so, it can be concluded that proposed driving cycle was acceptable.Publication Metadata only Modeling of Hybrid Wind-Gas Power Generation System and Adaptive Neuro-Fuzzy Controller to Improve the System Performance(WILEY, 2010) ERDAL, HASAN; Oguz, Yuksel; Guney, Irfan; Erdal, HasanIn this study, dynamic modeling of the hybrid wind-gas power generation system (HWGPGS) is realized by using the MATLAB/Simulink program for purpose of meeting the electric energy needs of small settlement units far from city centers or energy distribution networks. Besides, Adaptive Neuro-Fuzzy Inference System (ANFIS) is used to ensure electrical output magnitudes of the hybrid power generation system at a desired operating performance. The components that build up the hybrid power generation system and its functions in the system are explained. In case the HWGPGS is loaded with different consumer loads, analysis of electrical magnitudes of the system is made through simulation results. As it can be seen from the results of simulation study realized for the hybrid power generation system, output electrical magnitudes of the ANFIS controlled system reach to desired operating values in a short time. (C) 2009 Wiley Periodicals: Inc. Comput Appl Eng Educ 18: 669-683, 2010: View this article online at wileyonlinelibrary.com; DOI 10.1002/cae.20271Publication Metadata only Trajectory tracking performance comparison between genetic algorithm and ant colony optimization for PID controller tuning on pressure process(WILEY, 2012) ERDAL, HASAN; Unal, Muhammet; Erdal, Hasan; Topuz, VedatThe main goal of this study was to compare the performances of genetic algorithm (GA) and ant colony optimization (ACO) algorithm for PID controller tuning on a pressure control process. GA and ACO were used for tuning of the PID controller when predefined trajectory reference signal was applied. Offline learning approach was employed in both GA and ACO algorithms. Realized pressure process dynamic has nonlinear behavior, thus system was modeled by nonlinear auto regressive and exogenous input (NARX) type artificial neural network (ANN) approach. PID controller was also tuned by ZieglerNichols (ZN) method to compare the results. A cost function was design to minimize the error along the defined cubic trajectory for the GA-PID and ACO-PID controller. Then PID controller parameters (Kp, Ki, Kd) were found by GA-PID, ACO-PID algorithms, which were adjusted with their optimal parameters. It was concluded that both ACO and GA algorithms could be used to tune the PID controllers in the pressure process with excellent performance. This material is suitable for an engineering course on neural networks, genetic algorithm, ant colony optimization and process control laboratory. (c) 2010 Wiley Periodicals, Inc. Comput Appl Eng Educ 20: 518528, 2012