Yazar "Ekici, Yunus Emre" seçeneğine göre listele
Listeleniyor 1 - 5 / 5
Sayfa Başına Sonuç
Sıralama seçenekleri
Öğe Batarya yönetim sistemleri(İnönü Üniversitesi, 2019) Ekici, Yunus EmreBu tez çalışmasında elektrikli araçlar teknolojisinde önemli bir yere sahip olan batarya yönetim sistemi, farklı pil kimyaları ve hibrit bir elektrikli araç kullanılarak simule edilmiş ve bir batarya yönetim sistemi modellemesi yapılmıştır. Pil kimyalarına göre literatürde farklı batarya yönetim sistemi geliştirilmiştir fakat farklı pil kimyalarının tek bir batarya yönetim sistemi ile kontrolü henüz sağlanamamıştır. Gerilim seviyelerinin ve kapasitelerinin farklı olması bataryaların ortak bir yönetim sisteminden yönetilmesini zorlaştırmaktadır. Bu durum elektrikli araç teknolojisindeki temel problemlerden biridir. Yapılan çalışmada dört farklı kimyaya sahip olan (Lityum Demir Fosfat, Nikel Metal Hidrit, Nikel Kadminyum ve Kurşun Asit) piller, batarya paketleri haline getirilip aynı batarya yönetim sistemi ile iki farklı şekilde kontrol edilmiştir. İlk olarak sabit bir DC besleme ile tüm bataryaların şarj işlemleri gerçekleştirilmiştir. İkinci olarak bataryalar hibrit bir elektrikli araç modeline entegre edilip araç hareket halinde iken deşarjı sağlanmış ve daha sonra jeneratör ile şarj edilmiştir. Her iki durumda da batarya yönetim sisteminin çalışması analiz edilmiştir. Bu tezde yapılan çalışmalar neticesinde elektrikli araç teknolojilerinin temel problemlerinden biri olan farklı kimyalara sahip bataryaların tek bir batarya yönetim sistemi ile kontrol edilmesi incelenmiştir. ANAHTAR KELİMELER: Batarya yönetim sistemi, bataryalar, elektrikli araçlar, lityum piller, nikel piller.Öğe Efficiency Analysis of Various Batteries with Real-time Data on a Hybrid Electric Vehicle(2021) Ekici, Yunus Emre; Dikmen, İsmail Can; Nurmuhammed, Mustafa; Karadağ,TeomanBattery selection remains an up-to-date engineering problem for hybrid and electric vehicle manufacturers. Type of battery and its capacity will depend on the trip and vehicle parameters. An electric vehicle produced with the ideal bat-tery type will undoubtedly be preferred by customers. Data collected from black boxes of trolleybuses operated by Malatya Metropolitan Municipality were used in this study. The real road and driver characteristics were included in the study with the experimentally obtained data. These data are the accelerator pedal data obtained from vehicles driven by different drivers in regular and congested traf-fic hours. In this study, four different battery chemistries were run separately on a hybrid vehicle model and analyzed. Chosen battery chemistries are the most commonly used by manufacturers. These are Lead Acid, Nickel Cadmium, Nickel Metal Hydride and Lithium Iron Phosphate batteries. The results of the study are presented in detail comparatively. Among the battery chemistries, Lithium iron phosphate is observed to be the most ideal battery type for hybrid electric vehi-cles.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 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 A Review on Electric Vehicle Charging Systems and Current Status in Turkey(2021) Karadağ, Teoman; Nurmuhammed, Mustafa; Ekici, Yunus Emre; Dikmen, İsmail CanThe reality of global warming brings along an increase in environmental aware-ness. In recent years, this awareness has shifted public focus on electric vehicles. For a large group of people greenhouse gas emission is attributed to internal combustion engines. However, some challenges have arisen for electric vehicles. Limited range due to immature battery technologies and insufficient fast charging technologies that do not meet end user expectations are some major obstacles to overcome. Eventual-ly this situation negatively affects the sales and the wide use of electric vehicles. That is the reason why studies on wired and wireless charging systems play an important role in improving the sales performance of electric vehicles. In this study a thorough review of worldwide electric vehicle charging systems is conducted and discussed in the framework of the electric vehicles, charging stations, installations, and implemen-tation of standards in Turkey. The distribution of charging stations in Turkey are analyzed with respect to location, region, type, infrastructure requirements and future projections. The historical development of charging technologies, modes and charge levels have been studied in detail. As highlight of this study, wireless charging tech-nologies were also discussed and the historical development process was analyzed along with related standards. The current state of electric vehicle sector and charging stations in Turkey are discussed and provided with up to date information.
