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Öğe Control method simulation and application for autonomous vehicles(Ieee, 2018) Arikan, Abdullah; Kayaduman, Abdulsamed; Polat, Suat; Simsek, Yasin; Dikmen, Ismail Can; Bakir, Hincal Gokhan; Karadag, TeomanAutonomous vehicles can be operated without the need for human intervention by perceiving their physical environment, thanks to their automatic control systems. At present, extensive studies on autonomous land, sea, and air vehicles are ongoing all around the world. This project is focused on autonomous land vehicles. In the simplest examples, the speed and position of the vehicle can be controlled with the position sensor in the front wheel section and the speed sensors in the rear wheel section. Autonomy is achieved by generating signals for the control system by interpreting the data from various sensors on the vehicle with the aid of an algorithm. Different control methods can be applied for such vehicles. Within the scope of this project, the control of the vehicle will be provided by PID (Proportional-Integral-Derivative) control method, in order to constitute a basis for autonomous vehicle technology,Öğe Design and implementation of ultrasonic sonar system for autonomous vehicles(Ieee, 2018) Seven, Sibel; Dikmen, Ismail Can; Karadag, Teoman; Bakir, H. Gokhan; Abbasov, TeymurazAutonomous vehicles are vehicles that contain a variety of sensors that sense the environment and that can be actuated without driver intervention thanks to these sensors. Researches on autonomous vehicle technology continues at full speed. In this study, data from ultrasonic sensor and the temperature sensor are processed in the micro controller and displayed on the computer screen. For this, the microcontroller controls both the servo motor, calculates the sound velocity in the environment, and encodes the signal to be transmitted from the ultrasonic sensor. In this case, more accurate results are obtained than using fixed sound speed. In addition, the encoding of the signal sent from the ultrasonic transmitter is also prevented from being affected by noise or other sensors in the environment. This study was designed and conducted for the model vehicle to be used for autonomous vehicle studies in the laboratories of our university.Öğe Designing and Analysing of Ferrofluid Core Transformer(Ieee, 2018) Kartaca, Kubra; Abbasov, Teymuraz; Karadag, Teoman; Ekici, Y. E.; Dikmen, I. CanIn this study, the design of the magnetic fluid core transformer, which is a new approach and the characteristics of the output voltage values at different frequencies are investigated The Output voltage characteristics at different frequencies are investigated by adding magnetic fluid into the air-core transformer made of non-magnetic material The results are presented in tables and graphs. It is observed that at high frequency values, the electrical characteristics and the output characteristics of the designed prototype transformer are similar to those of industrial transformers. It has been concluded that magnetic fluid core transformers are advantageous in some applications in comparison with solid metal core transformers. Results are presented comparatively.Öğe Development and application of sensor network for autonomous vehicles(Ieee, 2018) Kayaduman, Abdulsamed; Arikan, Abdullah; Dikmen, Ismail Can; Bakir, Hincal Gokhan; Karadag, Teoman; Abbasov, TeymurazAutonomous vehicles are self-driving vehicles by interpreting data gathered from the environment through sensors. A set of sensors on the vehicle collects the raw data from the environment in which the vehicle is interacting. The software algorithms interpret the data from the sensors and generate commands for the vehicle to follow the path, change direction and maneuver. In this project, the data from the camera module and various sensors were processed and interpreted by means of software libraries on a network composed of micro controllers. Camera modules and image processing algorithms are used to detect strips along the roadside. The resulting images and the data from the other sensors generate the necessary commands for the vehicle's movement with a pivotal software formed on the embedded system. By this means the model autonomous vehicle gain self-motion capability by perceiving its surroundings.Öğe Diffusion separation of submicron particles by using magnetized spheres(Taylor & Francis Inc, 2023) Karadag, TeomanThe diffusion capture of submicron-sized particles in the gradient field formed by the magnetized ferromagnetic spheres in the external homogeneous magnetic field has been theoretically investigated. Magnetic field measurements were made with a specially designed prototype magnetometer. The simple semi-empirical formula of the magnetic force acting on the submicron particle was determined. The analytical solution of the diffusion equation for steady states was obtained. The concentration distribution of the particles in capturing regions was determined. A formula was obtained to evaluate the critical size of the submicron particles captured in this area. The effects of magnetic, hydrodynamic and geometric parameters of the investigated system on the critical size of the particles in the diffusion event were evaluated. The critical size of the particles decreased with the increase of the external magnetic field and was found to be independent of the dimensions of the spheres. As a result; the diffusion separation phenomenon in the gradient field formed by the magnetized ferromagnetic spheres is more effective than in the gradient magnetic field formed by the wires. The results obtained contribute to the development of the theory of magnetic separators using ferromagnetic matrix elements.Öğe Electrical Method for Battery Chemical Composition Determination(Ieee-Inst Electrical Electronics Engineers Inc, 2022) Dikmen, Ismail Can; Karadag, TeomanStorage of electrical energy is one of the most important technical problems in terms of today's technology. The increasing number of high-capacity high-power applications, especially electric vehicles and grid scale energy storage, points to the fact that we will be faced with a large number of batteries that will need to be recycled and separated in the near future. Additionally multi-chemistry battery management systems that enables the collective use of superior features of different batteries with different chemical composition. Here, battery chemical composition determination emerges as a technical problem. In this study, an alternative method to the currently used methods for categorizing batteries according to their chemistry is discussed. As the foundation, batteries with four different chemical composition including Lithium Nickel Cobalt Aluminium Oxide, Lithium Iron Phosphate, Nickel Metal Hydride, and Lithium Titanate Oxide aged with a battery testing hardware. Fifth, is Lithium Sulphur battery which is simulated. Brand new and aged batteries are used in experimental setup that is consist of a programmable electronic DC load and a software developed to run the algorithm on it. According to the algorithm, batteries are connected to two different loads one by one and voltage-current data are stored. Collected data are pre-processed by framing them and framed data are processed with a separation function. Eventually, the determination problem is converted to a classification problem. In order to solve this, artificial neural network and classification tree algorithms are applied. Because the artificial neural network algorithm is applied in previous studies and the high computational cost of it is presented; classification tree algorithm is concluded to be more applicable especially on low-power microcontroller applications. Consequently, 100% accuracy for battery chemical composition determination is achieved and results are presented comparatively.Öğe Electromagnetic field pollution measurements and mappings in a university settlement(Ieee, 2018) Keskinkilinc, Ugur; Arikan, Abdullah; Kizilaslan, Busra; Tekin, Sinem; Komurkara, Turgut; Kilinc, Elif; Karadag, TeomanImmediate measurements of electric field strengths of electromagnetic field sources operating at very high frequencies on all floors of 15 faculties, 5 institutes, 2 colleges, cafeterias, research laboratories buildings located in the center campus of Inonu University were carried out in the frequency range of 100 kHz - 8 GHz. In this context, the electric field intensity values were measured by Wavecontrol SMP Meter device approximately at 35 thousand locations between October and December of 2017. With the results obtained, electromagnetic field pollution maps were drawn. In this study, the faculties which have relatively high electric field strength values wereincluded. We have not measured a value that is appropriate for all of the criteria we have made and that is accurate to the limit values compared to the current standards.Öğe Estimation of Magnetization Properties of the Ferromagnetic Poly-Granular Beds(Taylor & Francis Inc, 2010) Karadag, Teoman; Yildiz, Zehra; Sarimeseli, Ayse; Abbasov, TeymurazIn this article, magnetizing properties of the packed beds that are constructed from the mixture of the ferromagnetic spheres of various sizes, pieces of wires and chips are investigated both experimentally and theoretically in order to determine the effect of the volumetric packing factor on the magnetizing properties of the bed. The average magnetizing curve has been determined by maintaining the external homogeneous magnetic field (H) higher than 150kA/m.Öğe A large-scale measurement, analysis and modelling of electromagnetic radiation levels in the vicinity of GSM/UMTS base stations in an urban area(Oxford Univ Press, 2016) Karadag, Teoman; Yuceer, Mehmet; Abbasov, TeymurazThe present study analyses the electric field radiating from the GSM/UMTS base stations located in central Malatya, a densely populated urban area in Turkey. The authors have conducted both instant and continuous measurements of high-frequency electromagnetic fields throughout their research by using non-ionising radiation-monitoring networks. Over 15 000 instant and 13 000 000 continuous measurements were taken throughout the process. The authors have found that the normal electric field radiation can increase similar to 25 % during daytime, depending on mobile communication traffic. The authors' research work has also demonstrated the fact that the electric field intensity values can be modelled for each hour, day or week with the results obtained from continuous measurements. The authors have developed an estimation model based on these values, including mobile communication traffic (Erlang) values obtained from mobile phone base stations and the temperature and humidity values in the environment. The authors believe that their proposed artificial neural network model and multivariable least-squares regression analysis will help predict the electric field intensity in an environment in advance.Öğe LONGTERM ELECTROMAGNETIC FIELD MEASUREMENTS AND POLLUTION MAPS IN A UNIVERSITY CAMPUS(Pamukkale Univ, 2014) Karadag, Teoman; Ozdemir, Ali Riza; Abbasov, TeymurazElectric field intensity emitted by electromagnetic field sources of the base stations in the campus of Inonu University and other very high frequency electromagnetic field sources' spread which are effect above at campus field were done and the frequency-based electromagnetic intensity maps of the campus were prepared. According to achieved measurement conclusions, the results were evalauted by comparing the periodical changes. The field intensity values of the electromagnetic waves which have different frequencies were measured by making a spectrum analysis over 450 points in the range of 27MHz-3GHz frequency in 2011. Also, in 2013, electric field intensity values were measured with instant measurements over 6700 points in the range of 100kHz-8GHz frequency. The electromagnetic pollution maps were drawn with obtained electric field values and the results were evaluated. One of study aims, it was determined changing electric field intensity along two-year period in campus of university. Another one purpose is provided homogeneous distribution of electric field source at this area with electromagnetic pollution maps which are drawn by obtained datas from results of measurements, and determined possible risk areas.Öğe Modeling of particle-capture mechanism of axial magnetic filter in bounded flow field with variable viscosity(Taylor & Francis Inc, 2020) Karadag, Teoman; Bakir, Hincal GokhanThe capture mechanism of micron-sized magnetic particles from a surfactant-containing suspension is examined in an axial magnetic filter with a bounded flow field by using the particle trajectory model. The effects of change in the suspension viscosity to the suspension flow velocity are modeled. Analytical and numerical solutions for the particle trajectory model are obtained for a laminar flow regime. It is evaluated that the magnetic particles in the suspension, subjected to a viscosity change, are captured in a gradient magnetic field formed by a magnetized external ferromagnetic wire and the capturing of particles gets harder due to condensation of surfactant layers.Öğe Modified Archimedes optimization algorithm for global optimization problems: a comparative study(Springer London Ltd, 2024) Nurmuhammed, Mustafa; Akdag, Ozan; Karadag, TeomanArchimedes Optimization Algorithm (AOA) is a recent optimization algorithm inspired by Archimedes' Principle. In this study, a Modified Archimedes Optimization Algorithm (MDAOA) is proposed. The goal of the modification is to avoid early convergence and improve balance between exploration and exploitation. Modification is implemented by a two phase mechanism: optimizing the candidate positions of objects using the dimension learning-based (DL) strategy and recalculating predetermined five parameters used in the original AOA. DL strategy along with problem specific parameters lead to improvements in the balance between exploration and exploitation. The performance of the proposed MDAOA algorithm is tested on 13 standard benchmark functions, 29 CEC 2017 benchmark functions, optimal placement of electric vehicle charging stations (EVCSs) on the IEEE-33 distribution system, and five real-life engineering problems. In addition, results of the proposed modified algorithm are compared with modern and competitive algorithms such as Honey Badger Algorithm, Sine Cosine Algorithm, Butterfly Optimization Algorithm, Particle Swarm Optimization Butterfly Optimization Algorithm, Golden Jackal Optimization, Whale Optimization Algorithm, Ant Lion Optimizer, Salp Swarm Algorithm, and Atomic Orbital Search. Experimental results suggest that MDAOA outperforms other algorithms in the majority of the cases with consistently low standard deviation values. MDAOA returned best results in all of 13 standard benchmarks, 26 of 29 CEC 2017 benchmarks (89.65%), optimal placement of EVCSs problem and all of five real-life engineering problems. Overall success rate is 45 out of 48 problems (93.75%). Results are statistically analyzed by Friedman test with Wilcoxon rank-sum as post hoc test for pairwise comparisons.Öğe A Novel Energy Consumption Prediction Model of Electric Buses Using Real-Time Big Data From Route, Environment, and Vehicle Parameters(Ieee-Inst Electrical Electronics Engineers Inc, 2023) Ekici, Yunus Emre; Akdag, Ozan; Aydin, Ahmet Arif; Karadag, TeomanElectric vehicles (EVs) have positive impacts on reducing oil dependence and exhaust emissions. However, the range problem of EVs is a factor that raises concerns for individual users and bus operators. For this reason, studies on increasing the range of the electric buses in public transportation is extremely important to ensure optimum operation. In this study, a novel energy consumption model, MTECM (Malatya Trolleybus Energy Consumption Model), is developed using the multi-parameter linear regression method. The real-time big data was collected on the field of Trolleybus vehicles, which have been operated for 8 years in Malatya / Turkiye. Firstly, by calculating the correlation of the parameters affecting this model, the parameters that are suitable for the purpose of our study are determined and regression analysis is performed on the original Trolleybus dataset. A total of 75.497.472 data are analyzed for this model. The RMSE (Root Mean Square Error) of MTECM is calculated as 0.29996. The trained model is applied to the 10 busiest routes in Malatya in terms of passenger density. The RMSE value on these routes is calculated between 0.30299 and 0.31421. Based on the results, with lower error rates, the proposed novel model is more efficient than other studies in the literature. In addition, energy consumption can be calculated for any route planned to establish an electric bus operation with MTECM. Therefore, according to the consumption obtained, the correct determination and selection of parameters that significantly affect the investment cost such as route, vehicle length, engine power, and battery capacity can be made.Öğe A novel modified Archimedes optimization algorithm for optimal placement of electric vehicle charging stations in distribution networks(Elsevier, 2023) Nurmuhammed, Mustafa; Akdag, Ozan; Karadag, TeomanThe number of electric vehicle charging stations (EVCSs) is increasing alongside electric vehicles (EVs). The unplanned rollout of EVCSs can lead to problems such as deterioration of the voltage profile, increased active power losses, and maximum load demand in distribution networks (DNs). Therefore, EVCSs should be placed in optimum locations on the DNs. The complexity of the problem requires efficiency and performance. In this paper, a novel modified Archimedes optimization algorithm (MAOA) is proposed for optimal placement of EVCSs in DNs. Five parameters of the AOA were modified using the Honey Badger Algorithm (HBA). This placement is based on a combination of indexes: power loss, voltage deviation, and voltage stability index (VSI). Next, Newton-Raphson based load flow analysis is used to compute the minimum cost. MAOA, AOA and eight other optimization algorithms are compared. The results provide the most appropriate buses in the DN. The efficiency of the proposed algorithm was tested on IEEE 33, 69, and 10-bus Hatay power network systems. In all test systems, the proposed MAOA provided the best results with consistently low standard deviation values. The results suggest that the proposed method is more effective in the integration of EVCSs into the DN. (c) 2017 Elsevier Inc. All rights reserved.Öğe A Novel Newton Raphson-Based Method for Integrating Electric Vehicle Charging Stations to Distribution Network(Aves, 2023) Nurmuhammed, Mustafa; Akdag, Ozan; Karadag, TeomanElectric vehicle sales are rising due to numerous factors such as government policies, falling prices, advanced, and eco-friendly technology. Built-in battery packs are charged using the energy from the distribution network. When a large number of electric vehicles are simultaneously charged with high power, the distribution network can be adversely affected. Differences in electricity supply and demand on the distribution network, voltage imbalance, and power losses are among the examples of effects. In this study, a mathematical model has been proposed in order to properly handle the effects of charging stations on the distribution network. According to the model, the optimum placement of electric vehicle charging stations is achieved within the constraints of the distribution network. In order to prove the robustness and validity of this model, the proposed model is applied to IEEE 33-bus radial test system. Results are discussed in cases.Öğe Optimization of Proportional-Integral-Derivative Parameters for Speed Control of Squirrel-Cage Motors with Seahorse Optimization(Aves, 2024) Ekici, Yunus Emre; Akdag, Ozan; Aydin, Ahmet Arif; Karadag, TeomanThe two different motion behaviors of seahorses in nature served as inspiration for the seahorse optimization (SHO) method, which is a new metaheuristic swarm intelligence-based approach to solving fundamental engineering problems. In this study, the propo rtion al-in tegra l-der ivati ve (PID) parameters for the simplified speed control of the manipulator joint using squirrel-cage induction motors were calculated with the SHO algorithm. As a result of these calculations, Kp, Ki, and Kd values were obtained as 0.0430, 0.00474, and 0.03254, respectively. Then, the time for the squirrel-cage motor to reach 50 rpm (revolutions per minute) and 90 rpm was calculated with the help of SHO. In PID + SHO operation, the squirrel-cage electric motor reached 50 rpm in 3 seconds and 90 rpm in 8 seconds. In this study, in which the SHO optimization method was used, it was calculated that the acceleration of the squirrel-cage motor and reaching the desired value gave 50% better results compared to the particle swarm optimization algorithm.Öğe The production and electrochemical properties of N-doped porous carbon structure-based supercapacitor coin cells and flexible wristbands(Elsevier, 2022) Bugday, Nesrin; Altin, Serdar; Karadag, Teoman; Yasar, SedatAmorphous zeolitic imidazolate framework (aZIF) materials were used for N-doped porous carbon material (NPC-1000) by thermolysis process and the KOH activation process was used to obtain high surface area (APC750). Symmetric supercapacitor devices were assembled with NPC-1000 and APC-750 as electrodes. The capacitance of the devices exhibited good specific capacitance 30.3 and 63.3 F/g, 1 V, respectively, and very high cycling performance (4000 continuous charge-discharge) with 0.13 capacitive fade. Due to the need for portable and wearable electronics in daily life, flexible or wearable energy storage devices have become the focus of attention in recent years. To demonstrate the practical application of the symmetric supercapacitors, the electrochemical properties of APC-750 were investigated and it was used for the assembling of a flexible wristband. The angle dependence of the capacity of a flexible wristband was analyzed and it is found that the best capacity was obtained for the angel of 180. The results showed that activated porous carbon material (APC-750) synthesized from aZIF has a high potential for supercapacitor applications when compared the NPC-1000 in this study.
