LEE- Mekatronik Mühendisliği-Yüksek Lisans

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http://hdl.handle.net/11527/19386

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Energy-efficient velocity trajectory optimization using dynamic programming for electric vehicles

( 2021-10-22) Kızıl, Abdullah ; Sezer, Volkan ; 518161030 ; Mechatronics Engineering ; Mekatronik Mühendisliği

The electrification and autonomous systems developed in the automotive industry in the last decade bring different solutions. Many methods have been developed and still continue to be developed to reduce energy consumption in vehicles, especially with electrified, connected vehicle technologies and navigation systems. Speed trajectory optimization is part of these methods. The main motivation of speed trajectory optimization is to prevent excessive energy consumption due to driver driving style. In order to prevent this, information such as the slope and speed limit of the road to be traveled is used over the navigation system. When we consider only energy while optimizing the speed trajectory, the prolongation of the driving time will appear as a concern. Because if the vehicle goes faster, the energy consumed will increase quadratically. Therefore, optimization will always demand the vehicle to go slower in order to consume less energy and there must be a balance between energy and travel time. In this thesis, a study has been carried out that periodically updates the speed trajectory, which will ensure that the destination point and arrival time information are provided into the navigation system by the driver while consuming the least energy in the given time. The dynamic Programming (DP) method is used to solve this problem. Dynamic programming always presents the global optimum behavior under the given boundary conditions. The speed of the vehicle was used as the only state variable and its optimization was performed separately over the distance stages. The average speed required to reach the destination on time, based on the destination point and travel time information obtained from the navigation system, is given as an input to the optimization, and the DP state space is constantly updated. The main reason for this is to reduce the memory load required by DP. Thus, a fixed number of states are scanned. But the scanned range values are updated according to this speed input. A longitudinal vehicle model was used for optimization. The limits of the powertrain are also part of the optimization as a boundary condition. Before the optimization is run, a pre-calculation is also made to include the states where the transition between states is possible only in the optimization. Thus, it is aimed to shorten the calculation time by not including the unreachable situations in the optimization. Optimization takes place along a certain horizon. The speed trajectory calculated for this horizon is transmitted to the vehicle speed control unit as an input. The vehicle follows this speed profile. The optimization is updated again after a certain period of time and transmits the speed trajectory calculated for the next horizon to the vehicle. The purpose of this is if the vehicle cannot follow the given speed for any reason during real driving, the optimization is performed again based on the new conditions. This allows the vehicle to progress in real-time using the speed trajectory closest to the global optimum. In the study, simulation and analysis of the all-electric truck were carried out on two different slope routes. Tests were performed with different fixed velocity values and velocity profiles produced by velocity trajectory optimization in both routes. As a result of the simulations carried out, it has been observed that up to 4% of energy consumption and up to 2.5% of the targeted time are saved. Thanks to the proposed adaptive weight factor, it has been observed that the time-energy balance is maintained for different routes, arrival times, and vehicle parameters.
Predictive powertrain control

(Graduate School, 2022) Lalek, Ufuk ; Üstoğlu, İlker ; 755241 ; Mechatronics Engineering Programme

The main purpose of this study is to design predictive powertrain controller that finds optimal gear and optimal pedal position to minimize the fuel consumption based on the given road data. Model predictive control (MPC) method is used as the controller. Dynamic programming (DP) method is selected as the optimization solver of the algorithm due to the discrete structure of the gear states. Within the scope of this thesis, it is also aimed to develop a truck model with automated manual transmission (AMT) gearbox that can be controlled via MATLAB. The simulation environment is AVL Cruise and MATLAB/ Simulink. AVL Cruise is a powertrain simulation program that allows users to model a variety of powertrains using a specific library of modules. It is used to create the plant model and test it out with various drive cycles. The plant model is evaluated using MATLAB/ Simulink via interface block in the AVL Cruise program and transmission control algorithm which is developed in MATLAB based on the model predictive control method.
Retrieving and classifying emergency situations for smart home applications

(Graduate School, 2022) Uçar Mavi, Seher ; Doğan, Mustafa ; 738349 ; Mechatronics Engineering Programme

One of the uses of Bluetooth, which is a wireless communication technology, is to communicate with smart devices in order to increase the functionality of not very advanced electronic devices and to carry data that appeals to the user. Bluetooth has also paved the way for devices without internet access to access the internet at a much lower cost by communicating wirelessly with devices with internet access. Data transferred to the Internet can be stored and used for any purpose. However, while doing this, user data must be kept encrypted by law and should not be shared with third parties. In this study, it has been investigated how user data can be shared with authorized institutions for emergencies. A mesh network was created using the Cypress BT-Mesh kit. Each of the 4 development boards is programmed to simulate a smart home device. Cypress's Software Development Kit(SDK) was used during programming. In addition, an Arduino GPS system included in the system is used to receive location data. The RSA (Rivest-Shamir-Adleman) algorithm is used to send all user data encrypted to authorized institutions in case of emergency. Thus, both the confidentiality was not violated and the emergency situation was reported to the authorized institutions and the user. The RSA algorithm was executed on the Espressif processor and the ESP-IDF SDK was used. Assuming that the decryption process is carried out in the cloud environment of the institutions, a scenario in which institutions intervene by looking at the lookup table and comparing them is considered. In this study, the scenario of notifying the fire department in case of fire and informing the police in case of a thief is simulated. In the simulation, it is shown how user data can be sent in an encrypted way. When the functioning of the network and the transmission of data are examined, it is concluded that the RSA algorithm provides a high-security solution for smart home applications. Thus, it has also been proven that a recovery notification use-case can be added to a smart home system without violating privacy.
Design and control of ros based omnidirectional vehicle

(Graduate School, 2022) Nalbant, İbrahim Dinçer ; Temeltaş, Hakan ; 710624 ; Mechatronics Engineering Programme

Nowadays, with the fact that the hardware and software of mobile robots are cheaper and easier to find, studies on them have increased, and as a result of research and development activities carried out by academia and large companies, mobile robots have been widely used in the areas such as exploration, humanoids, drones, automation, transportation, space missions, patrolling, search and rescue and service robots. In addition, a wide variety of driving systems have been designed to increase the driving characteristics of mobile robots, as well as sensors and software architectures to make them autonomous. In this thesis, a mecanum wheeled, ROS-based autonomous, omnidirectional vehicle prototype with high load carrying capacity, called ITU omnidirectional vehicle, has been designed and produced to be used in future research and development activities at the ITU Robotics Laboratory. ITU omnidirectional vehicle is capable of moving to all directions on the ground plane without changing its heading angle, with the help of its specially designed mecanum wheels. Mecanum wheels are driven individually by four Maxon DC motors. For the autonomous navigation, there are two Hokuyo LIDAR sensors and a Xsens IMU sensor mounted in the vehicle. Vehicle inverse and forward kinematic analyses were carried out according to the mecanum wheel kinematics and chassis dimensions, then these equations were applied to the control software of the vehicle. DC motor selection of the vehicle was made according to the payload and acceleration values needed. A special drivetrain was designed between motors and wheels to reduce the lateral force, vibration and balancing effects of the mecanum wheels to the motors. Electrical design of the vehicle was made by using DC regulators and supplying appropriate power for the hardware. For the software of the vehicle, open source Robot Operating System(ROS), was integrated to the vehicle, so that various control, localization, path planning and mapping algorithms could be developed and tested. Both simulation and experimental results of different path following scenarios for the vehicle is presented in the last chapter of this thesis. Results of these case studies satisfied the requirements of the thesis.
Nominal capacity calculation for lithium-ion batteries with advanced algorithms

(Graduate School, 2022) Nalbant, Harun ; Gökaşan, Metin ; 735121 ; Mechatronics Engineering Programme

The speed of global warming and demand for energy increased rapidly after Industrial Revolution by high energy usage for the current high-level technologies. The automotive industry is one of main industries demanding high energy resources to grant quality transportation. However, due to this high usage of energy, the Carbon emissions rapidly increased due to fossil-fuel usage. Many countries adjusted their emission regulations to decrease the devastating effects of global warming. Therefore, many automotive producers started to search for technologies to comply with these strong regulations. Electric vehicles emerged from these regulations. In addition to that, the comfort and the decreased complexity of the design in the electric vehicles are also very appealing for the people which means lower effort on the service needs. Therefore, it is expected that the number of electric vehicles (EVs) will increase on the way. The main components for the electric vehicle are the propulsion and energy storage components. As a driver, there are 2 main parameters selecting a vehicle: Propulsion Power and Range. Propulsion power could be granted with a good electric motor and inverter design. On the other hand, EV batteries play a key role in increased range. The majority of the people generally focus on the range and usage instead of high-powers. Therefore, the point of focus in this study is the EV batteries. EV batteries are one of the main and most expensive components in the vehicle. The drivers mainly tend to use the vehicle as much as they can without any component change. However, as time goes on, the battery gets older and its performance would be decreased. Furthermore, an aged battery could harm the driver and the passengers. As battery developers tend to avoid any unwanted situation, the batteries are restricted to be used for a limited time. This limited-time is mainly dependent on battery State-of-Health (SOH). The SOH is the main indicator in a Battery Management System (BMS) to monitor the battery. The developers target to ensure a safe range for battery usage. On the other hand, the driver would like to challenge the limits to use the battery longer to avoid frequent battery-related service costs. State-of-Health of the battery determines the battery life cycle. If a battery is aged due to driving, temperature and cycle conditions, then, the usage of that battery is restricted by the Battery Management System (BMS). To avoid failure due to ageing, there are some mechanisms to warn the driver before the battery fails so that any kind of incident is prevented. This restriction relies on the accuracy of the SOH calculation. In the automotive industry, the battery manufacturers' warranty period mainly depends on the battery SOH. In other words, if the actual SOH of the battery is lower than the guaranteed value, then, the warranty period is over. This SOH value is defined under the worst-case scenario. In other words, the calculation accuracy for SOH is added as an offset to the target value of the manufacturer. The worse value of SOH calculation accuracy would result in an earlier finish of the warranty period. In other words, better accuracy would result in a longer battery usage period. Better accuracy results in a longer warranty period. For example, the state-of-art batteries are generally guaranteed for 5 years under the condition SOH is calculated with %5 accuracy. If this accuracy is increased by ~% 3, then the battery life would be guaranteed for 1 more year. Since the battery technologies are growing, the warranty period could be more than 5 years which results in a higher increase based on SOH accuracy improvement. There are 2 main indicators for SOH: Capacity and Internal Resistance.
Automatic landing with model predictive control

(Graduate School, 2022) Ulukır, Talha ; Üstoğlu, İlker ; 518191029 ; Mechatronic Engineering Programme

In flight control systems, the landing maneuver is one of the most critical time periods for the aircraft, and it is of great importance to both respond to the disruptors and ensure durability in this time period when the disruptor activity is high. Within the scope of this thesis, 4 different controller type automatic landing systems were designed for a twin-engine passenger aircraft, this landing system provides fully automatic landing in both longitudinal and lateral planes. Within the scope of the thesis, different control architectures in the literature for the automatic landing autopilot were examined. Within the scope of the thesis, the change of system inputs and system outputs as a result of linearization under different conditions has been examined. The consistency of the nonlinear model of the aircraft with the linear model was compared, and this comparison was made by examining the behavior of the system variables in response to the binary commands given to the control surfaces. Within the scope of the thesis, what the sub-phases of the automatic landing autopilot are and according to which criteria and conditions these sub-phases are separated from each other are examined. The classical control architectures in the flight control system (stability-enhancing system and control-enhancing system) are discussed, and for what purposes and with what standards these architectures are designed. In fixed-wing aircraft control systems, the longitudinal and lateral states of the system are separable. In the scope of the thesis, the automatic landing architectures in the literature for these separated states are examined. The controllers designed for the descent system in the thesis are: PID, Linear Quadratic Integral, Model Predictive Control and Algebraic Model Predictive Control architectures. One of these four different control architectures (PID) is in a single-input-single-output control structure, while the other three control architectures (LQI, MPC, AMPC) are in a multi-input-multi-output control structure.
Paletli araçlar için otomatik transmisyonun dinamik modeli, kavrama parametre adaptasyonu ve kontrolü

(Lisansüstü Eğitim Enstitüsü, 2022-02-17) Arı, Ali ; Yalçın, Yaprak ; 518171037 ; Mekatronik Mühendisliği

Bu tez çalışmasında; paletli askeri araçlarda kullanılan otomatik transmisyonların vites değiştirme fonksiyonlarını gerçekleştirecek elektronik kontrol ünitesi kontrol algoritmaları tasarlanmıştır. Bu algoritmaların, transmisyonun dinamik modeli ile desteklenmesi sayesinde planet dişli sistemindeki kavramalarda herhangi bir hız ve basınç sensörü olmadan kontrol için gerekli değişkenler hesaplanmıştır. Kavramaların aşınması durumunda, kavrama parametreleri, yalnızca transmisyon giriş ve çıkış hızı sensörlerinden gelen bilgileri kullanan bir adaptasyon algoritması aracılığıyla kestirilmiştir. Bir yenilik olarak, atalet fazında dinamometredeki kalibrasyon işlemlerini kısaltacak, dayanıklı ve hassas kontrole olanak sağlayacak, dinamikleri doğrusal olmayan transmisyon sisteminde kullanılabilen, genetik algoritma ile optimize edilmiş bir PID kontrol tasarımı yapılmıştır. Tasarlanan dinamik model, uyarlama algoritması ve kontrolör, bir MATLAB/Simulink-Simscape güç aktarma sistemi simülasyon modeli üzerinde test edilmiştir.
İleri sürücü destek sistemleri için bir fonksiyonel güvenlik uygulaması

(Lisansüstü Eğitim Enstitüsü, 2022-05-26) Çağlayan, Ebru ; Kurtulan, Salman ; 518201010 ; Mekatronik Mühendisliği

İleri Sürücü Destek Sistemleri üzerinde ISO 26262'nin halihazırda var olan versiyonunun yetersizliği sonucunda ortaya çıkan yeni bir fonksiyonel güvenlik metodolojisi gerekliliği sonucunda tezin ilk amacı ortaya çıkmıştır. Bu amaç, ISO 26262'nin bu yeni teknolojiye uyarlanabilir bir versiyonunu ortaya koymaktır. Bunun için, var olan ISO 26262 standardizasyonuna, İleri Sürücü Destek Sistemleri ve tarihçesine ve ISO 26262'nin uygulama adımlarına değinilmiştir. Akabinde, bütün bu bilgiler ışığında İleri Sürücü Destek Sistemlerinde yaygın bir sistem olan İleri Acil Frenleme Sistemi (AEBS) fonksiyonu üzerinde örnek bir çalışma gerçekleştirilerek uyarlanan metodoloji tanıtılmıştır. İleri Acil Frenleme Sistemi, genellikle radar ve kameranın birlikte kullanılarak otomobil, motosiklet, yaya ve bisiklet gibi hedeflerin birlikte algılandığı sensör füzyonunun aktif olarak kullanıldığı bir fonksiyondur. Radarlar otomobilleri seçme konusunda daha efektif iken, kamera yaya tipi hedefleri seçmede daha büyük başarı göstermektedir. Bütün bu algılamanın gerçekleştiği karmaşık sistemlerde fonksiyonel güvenliğin gerekliliği tartışılmazdır. Bununla birlikte yollarda meydana gelen kazaların çoğunluğunun sürücü dikkatsizliğinden kaynaklandığı düşünülürse İleri Acil Frenleme Sistemi gibi akıllı bir teknolojinin fonksiyonel güvenliğin gerçekleştirildiği koşullarda trafik kazalarını büyük ölçüde engelleyeceği gerçeği yadsınamazdır. Dolayısıyla tezde otomotiv sektörüne daha büyük bir fayda sağlaması bakımından örnek fonksiyon olarak İleri Acil Frenleme Sistemi fonksiyonu seçilmiştir. Tezde ikincil bir amaç olarak hem İleri Sürücü Destek Sistemlerinin hem de fonksiyonel güvenliğin sektörde önem kazanmasıyla birlikte trendleşen bu iki alanın terminolojisinin Türkçe bir tez vasıtasıyla literatüre kazandırılarak Türkçe bir kaynak elde etmek hedeflenmiştir. Bu bağlamda ayrıntılı görseller ve kısaltmalarla tez Türk otomotiv sektörü için bir kaynak oluşturmaktadır.
Çamaşır makinelerinde yapay sinir ağları ile yıkama performansı ve enerji tüketiminin modellenmesi

(Lisansüstü Eğitim Enstitüsü, 2022-06-23) Aktaş, Yakup ; Altınkaynak, Atakan ; Kalafat Acer, Merve ; 518181036 ; Mekatronik Mühendisliği

Dünyada gelişen teknoloji ve mühendislik yetkinlikleriyle beraber endüstride bir rekabet ortamı oluşmuştur. İlgili sektör üreticileri fark yaratan ürünler otaya koymak için gelişen teknolojik adımları yakalamak ve ürünlerine değer katacak gelişmeleri takip etmek durumundadır. Özellikle tüketicinin doğrudan etkileşim halinde olduğu beyaz eşya ürünlerinde fark yaratan teknolojiler ön plana çıkmaktadır. Ancak ürünlere eklenen birçok yeni özellik beraberinde maliyetleri de doğurmaktadır. Aynı zamanda üreticiler için kaynak ve zaman yönetimi anlamında da ekstra yük getirmektedir. Bu nedenle ürünlerin ar-ge, tasarım ve üretim süreçleri ne kadar iyileştirilebilirse sektörde rekabetçi ve yenilikçi ürünler ortaya koyabilmek o kadar mümkün hale gelecektir. Üretilecek olan ürünlerin ar-ge ve tasarım aşamalarındaki test süreçlerinin iyileştirilmesi maliyet, kaynak ve zaman açısından üreticiler için olumlu katkı sağlamaktadır. Çamaşır makinaları günümüzde yaygın olarak kullanılan dayanıklı tüketim aletleridir. Su ve elektrik enerjisi ile çalıştıkları için, test süreçlerinde her bir çevrimdeki bu tüketimler ek maliyetlere ve aynı zamanda dünya kaynaklarının da tüketilmesine yol açmaktadır. Bununla birlikte zaman açısından da yeni ürün proje süreleri uzamakta ve teknolojik gelişimi yavaşlatmaktadır. Yani test süreçlerinin kısalması, hem sürdürülebilirliğe katkı yapacak, hem maliyetleridüşürecek hem de zamanın verimli kullanılmasına yol açacaktır. Tez kapsamında çamaşır makinalarının ar-ge ve tasarım süreçlerinde gerçekleştirilen test metotlarının kurulacak model yapısında incelenmesi ile çevresel sürdürülebilirliğe katkı sağlanması, üretici maliyetlerinin düşürülmesi ve zaman tasarrufu elde edilmesi amaçlanmaktadır. Çamaşır makinalarının sahip olduğu özelliklerin yanında, standartlarca belirlenmiş çeşitli sınırları da sağlıyor olması gerekmektedir. Bunlardan biri yıkama performansıdır. Çamaşır makinalarının temel özelliği olan yıkama işlemi, standartlarda belirlenmiş yöntemlerile ölçülebilmektedir. Üretilen çamaşır makinalarının da belirlenen limit değerin altına düşmeyecek etkinlikte yıkama performansına sahip olması gerekmektedir. Üreticiler ise bu sınır koşulu sağlayıp sağlamadığını test etmek için standart yıkama performansı testlerini laboratuvar oertamında gerçekleştirmektedir. Ancak farklı sınır koşullarından dolayı yıkama performansını sağlayabilmek adına birçok parametrenin optimize edilmesi gerekmektedir. Birden fazla parametrenin etki ettiği yıkama performansı hedef değerini yakalayabilmek adına yapılan bu deneme testleri ise su ve enerji tüketimlerinden dolayı beraberinde ekstra bir yük getirmektedir. Bu sebeple kurulacak model yapısı ile bu test sonuçlarının tahmin edilebilmesi hedeflenmektedir. Diğer bir yandan, standart olarak sağlanması gereken yıkama performansının belirli enerji tüketimi sınırları içerisinde gerçekleşiyor olması gerekmektedir. Üreticiler, üretilen çamaşır makinasının enerji tüketiminin, standartlarda belirlenen enerji sınıf aralıklarından hangisine denk geldiğini deklare etmek durumundadır. Doğal olarak daha düşük tüketime sahip enerji sınıfındaki ürünler son kullanıcı tarafından daha çok tercih edileceğinden yıkama performansı değerine olabilecek en düşük enerji tüketimi ile ulaşmak ana hedeftir. Bu nedenle yapılan performans testleri yerine yıkama performansını tahmin edecek model ihtiyacının yanında, optimum tasarımın yapılabilmesi için enerji tüketiminin de tahmin edilmesi gerekmektedir. Kurulacak enerji tüketimi modeli ile de enerji tüketimi değerinin test yapmadan tahmin edilebilmesi amaçlanmaktadır. Tez kapsamında kurulacak yıkama performansı ve enerji tüketimi tahmin modellerini elde edebilmek için öncelikle deneysel veriye ihtiyaç vardır. Bu amaçla laboratuvar ortamında deney istasyonları hazırlanmış ve standart yıkama performansı test sonuçları tüm analog ve dijital verileriyle birlikte toplanmıştır. Tahmin edilmek istenen yıkama performansı ve enerji tüketimi değerlerinin yanında model yapılarını girdi sağlayabilecek parametrelerin de değişimleri kaydedilmiştir. Toplanan verilerin analizi yapılarak yıkama performansı ve enerji tüketimi tahmin modelleri için ayrı ayrı girdi parametreleri seçilmiş ve çeşitli model yapıları oluşturulmuştur. Oluşturulan yapılardan en iyi performans gösteren modeller seçilmiştir. Elde edilen modeller sayseinde yıkama performansı ve enerji tüketimi için seçilen girdi parametresi değerleri verildiğinde yüksek doğrulukta sonuçlar alınmaktadır. Tezin ilk bölümünde literatürde çamaşır makinalarında gerçekleştirilen yıkama prosesine etki eden temel parametrelerden bahsedilmiştir. Ayrıca tezin ilk bölümünde çamaşır makinlarında geliştirilmiş makine öğrenmesi, yapay sinir ağı ve bulanık mantık algoritma çalışmalarından örnekler sunulmuştur. Yapılan çalışmalarda tahmin edilmesi kritik parametrelere yer verilmiş ve farklı yöntemler kıyaslanmıştır. Tezin ikinci bölümünde yıkama performansı ve enerji tüketimi modellerine veri girişi sağlamak amacıyla kurulan deney sisteminden, kullanılan ekipmanlardan ve ölçüm yöntemlerinden bahsedilmiştir. Bu bölümde ek olarak toplanan deneysel veri kümesi incelenmiştir. Verilerin makina özellikleri açısından yıkama performansı ve enerji tüketimine göre dağılımları gösterilmiştir. Tezin üçüncü bölümüden yıkama performansı modeli için girdi parametreleri seçilmiştir. Girdi parametrelerinin çıktı değerine etkileri detaylıca açıklanmıştır. Parametrelerin istatistiksel özellikleri elde edilmiş, girdi-çıktı parametreleri arasındaki lineer korelasyon ilişkileri çıkarılmıştır. Tezin bu bölümünde lineer yöntemlerin problemi çözümlemeye yetmeyeceği ve makine öğrenmesi yöntemlerinin denenmesi gerektiği yapılan lineer regresyon analizleri ile vurgulanmıştır. Bu amaçla aynı bölümde modelleme için kullanılacak yapay sinir ağları ile Levenberg-Marquardt geri yayılım algoritması açıklanmıştır. Kurulacak modelin algoritma parametreleri detayları ile verildikten sonra farklı katman ve nöron sayılarındaki yapay sinir ağı sonuçları elde edilmiş ve en iyi performansı veren modeller belrtilmiştir. Yapay sinir ağı modeli Matlab programı kullanılarak Levenberg-Marquardt geri yayılım öğrenme algoritmasının model parametre detayları değiştirilerek oluşturulmuştur. Tezin dördüncü bölümünde de yıkama performansı yapay sinir ağı modeline benzer şekilde enerji tüketimi modeli için de girdi parametreleri belirlenip lineer korelasyon ilişkileri belirtilmiştir. Lineer regresyon analizi sonuçları paylaşılmış ve enerji tüketimi modeli için de yapay sinir ağı modeli kurulmuştur. Yıkama performansı yapay sinir ağı modeli ile aynı ağ yapısı özelliklerinde modeller karşılaştırılmış ve en yüksek performansı veren model seçilmiştir Tezin beşinci bölümünde elde edilen model yapıları, ortak model arayüzü oluşturmak adına Simulink ortamına aktarılmış ve tasarım süreçlerinde kullanıma hazır hale getirilmiştir. İlgili girdi parametrelerinin değerleri verildiğinde elde edilen en iyi modellerin tahmini sonucu yıkama performansı ve enerji tüketimi değerleri elde edilebilmektedir. Tezin beşinci ve son bölümünde ise yapılan tez çalışmasının sonucuna ve gelecek çalışmalar için önerilere yer verilmiştir.
Dynamic weighing method for checkweigher

(Graduate School, 2022-06-23) Gülbaş, Mustafa Can ; Yalçın, Müştak Erhan ; Ayhan, Tuba ; 518191025 ; Mechatronics Engineering

The main purpose of this study is to examine the checkweigher system. It is necessary to accurately estimate the weight of the product in motion with a checkweigher. This is an estimation process, as the measurement data obtained in motion will never be as clean as the static measurement data. The measurement error tolerance is limited by state regulations. Therefore, a dynamic weight measurement system should obey particular regulations in order to be used in industry. The automatic weight control system, checkweigher, which is used in many areas from production to shipment in the industry, consists of three conveyor belts, at least two photocells, load cell, processor, control screen for the user and rejector/router arms. In the system, the product carried by the in-feed conveyor belt is guided by the output conveyor belt after passing over the conveyor belt connected to the load cell. At this point, at the time of passing over the conveyor belt connected to the load cell, data is received by the load cell at a sampling frequency of 1600 Hz and sent to the processor for processing. The working principle of the load cell depends on the stretching and compression state of the resistors called strain gauges. When force is applied to a load cell, some resistors compress while others flex. When this change is converted to voltage, an inference can be made about the weight of the product. There are many noise factors that affect the measurement signal. The time-variant low-pass filter in the cascade form can effectively filter out the noise from the load cell signal, but quite a lot of filters are required to achieve high accuracy. In this study, a different approach was tried with a time-variant low-pass filter in order to accelerate measurements. The number of cascade form low-pass filter is optimized to shorten the response time while providing regulation-complaint measurement accuracy. By applying the filter, it is aimed to reach the mass of the product from the oscillations with minimum number of filters. The maximum speed obtained within the error limits was specified. As a result, by reducing the number of filters and increasing the damping, the weight data of product from the oscillations were reached faster within the error limits given in the regulation.
Uzun kısa süreli bellek ile altın fiyatı tahmini

(Lisansüstü Eğitim Enstitüsü, 2022-07-06) Birecik, Sina ; Günel Öke, Gülay ; 518181032 ; Mekatronik Mühendisliği

Thanks to its many physical and chemical properties, gold has been a mineral that has attracted the attention of people since ancient times. Although it has various usage areas such as the defense industry, electrical electronics industry, and jewelry, its economic value can be given as the most important feature from the first ages to the present day. With the use of gold in coins by the Lydians, gold became a tool of exchange and investment. It still maintains this feature today. Thanks to these features, it has become a symbol of power in societies. With the Bretton-Woods system, which came into effect towards the end of World War II, the gold price was indexed to the US dollar. With the increasing tension in the world markets, this system collapsed, and gold started to be priced dynamically as of 1971. The gold price in Turkey is calculated using the worldwide accepted gold price in US dollars and the Turkish lira / US dollar parity. Today, investors want to make a profit in the long or short term with minimum risk factors. The most risk-free investment instruments preferred by investors can be given as precious commodities such as gold, foreign currencies, stocks, real estate, cryptocurrencies, bonds, mutual funds, and government bonds. It is preferable to make estimates of the corresponding returns or losses on such investments. For this reason, forecasting is of great importance when investing and the reaction of investment instruments affected by events in the world should be analyzed. Our main purpose in this research is to predict the future behavior of gold based on past data. The recurrent neural network (RNN), which is a type of deep learning, was chosen as the forecasting method. The problem to be studied in this research is considered a regression problem that requires a nonlinear solution to the time series. In this study, feature selection and gold price prediction in multivariate financial time series were examined. There are many dynamic factors for pricing gold used for investment. Since not every factor has the same effect, the most effective factors on gold should be determined. After the data engineering part, the main factors affecting gold price have been identified. Features were determined using the factors examined, and the most important of these features were selected and formed the basis of the study. The datasets were created using various features such as the US dollar index, cryptocurrencies, commodities, stock market indices, volatility index, inflation, and interest rates. Although gold prices in the real-world act according to basic theory and criteria, gold is a commodity type that is affected by many technical and fundamental parameters. Before the forecasting section, feature selection was made using Random Forest Regression and Linear Regression. In this section, it has been determined that the parameters that affect the gold price the most are the USD/JPY parity, 10-year expected inflation (USA), 10-year real interest rate (USA), US gross national product (GDP), and the amount of USD in circulation. No improvement was observed in the forecasting performance criterion even if more variables were added. In the principal component analysis, the most important variables representing the main dataset were determined as oil, US real interest rate, Bitcoin, silver price, LME index, 10-year inflation (USA), TXBM index, USD money supply M1, and volatility index. A basic recurrent artificial neural network (RNN) and long short-term memory deep learning network (LSTM) were used in the forecasting study. The dataset combinations were created by using 5 variant variables on 3 main datasets so that there are 15 combinations in total. These variant variables are economic indicators LMACD and MACD. Test combinations were created using dataset combinations also batch size and window size values determined for RNN and LSTM networks. It has been tried to give an idea about the reaction of the gold price against these inputs. The window size is the hyperparameter that determines how many days the historical data will be retrieved when creating the observation unit. RNN and LSTM hyperparameters were also derived on each dataset combination and forecasting was made. After the training process, the predictive model performances of the applications were calculated. Parameters with appropriate estimation results were determined in the tests performed. While RNN performs at par with LSTM in one main dataset, LSTM has a higher predictive success than RNN in the other two main datasets. In tests where the datasets created by adding the MACD indicator were trained with lower window sizes, these models gave superior results than other combinations. In addition, it was observed that there were deviation errors in the training of the models due to the Covid-19 crisis, which started in March 2020. In the forecasting study on the training set, it was determined that the network could not perform as well as before this date in the part of the training data after the onset of Covid-19. To improve the model, the existing parameters were selected more precisely, and optimization was made. Although it is not possible to use it professionally yet, it has given promising results for the first study. In this context, the aim and scope of the study have been met. It will also be a starting point for future work.
Functional safety mechanism development of creep monitoring in automatic transmission

(Graduate School, 2022-12-28) Ardıç, Burak ; Üstoğlu, İlker ; 518191007 ; Mechatronics Engineering

Functional safety one of the most of important feature of new development lifecycle of the vehicle systems. ISO 26262 is known as "Road vehicles – Functional safety" which is an international standard for functional safety of electrical and/or electronic systems of road vehicles. This definition comes from International Organization for Standardization (ISO) in 2011 and revised in 2018. In today's powertrains, mostly modern automatic transmissions are used for road vehicles. Those transmissions have electronic systems that supports driver activities in better way. I.e., in manual transmission, driver has to control 3 pedal (clutch, acceleration and brake) and gear lever while driving but with help of automatic transmission, driver only controls 2 pedal (acceleration and brake) and usually gear lever always stay in D (Drive) or R (Reverse) based on which direction driver wants to move. In automatic transmissions, clutch pedal is controlled by electronic control units such as transmission control unit. One of the functional safety responsibilities is controlling these electronic control unit activities via different safety mechanism whether they work in proper and safety way. Because in case of wrong detections, wrong calculations in electronic control units or wrong requests of drivers might cause very dangerous severities. In this thesis, it is aimed to develop a functional safety mechanism that monitors the creep/Creep function of the automatic transmission and takes the necessary measures before the accidents caused by this function. Before starting of modelling this safety mechanism monitoring these functions in MATLAB/Simulink, firstly some functional safety concept development has to be done to define procedures. In this study, functional safety development is done based on V-model. Firstly, Item definition is done to define specification of item which is investigated. Since transmission control unit was our main item, all specifications that includes gear ratios, transmission maximum torque, clutch engagement information to transmit torque, communications with other electronic control units and also since transmission control unit is related to vehicle also operational driving and vehicle movement states are given. Then hazard analysis and risk assessment (HARA) is done to define potential hazards and operational situation which can be seen during creep function is investigated and safety goals are determined derived from ASIL. After safety goal determination, functional safety concept that includes safety mechanisms is done by defining functional safety requirements to fulfill safety goals. Before start on development of safety mechanism monitoring, all technical safety requirements are set with hardware and software with including architecture of system. To monitor creep function, in a first-place automatic transmission plant model which includes engine, transmission, vehicle, gear shift mechanism, and CAN/HW state model is implemented in MATLAB/Simulink platform. This plant model also includes a creep function to be monitored. In the plant model development phase, the transmission gear ratio is selected from the item and all other vehicle parameters as engine inertia, and engine and torque converter characteristic values are taken from the vehicle that is thought of as a concept. After functional safety concept development and plant model development, the safety mechanism of creep function monitoring is implemented based on defined safety requirements. The safety mechanism of creep monitoring is responsible for detecting high creep torque errors mainly for driver torque demand, engine torque from plant model, engine speed, and vehicle velocity. During creep, the transmission control unit can request increased engine idle speed/torque if needed or unintentionally close the lockup clutch. Both cases might cause unintended acceleration. The safety mechanism receives the engine torque from the plant model and calculates the consumed by the engine based on engine inertia and engine speed. The safety mechanism of creep monitoring checks the difference between engine torque from the plant model and consumed engine torque. This difference is accepted as creep torque which is the torque transmitted to wheels during creeping. If torque transfer is higher than the defined safety torque threshold for the allowed fault reaction time interval, then safe state which leads to force to bring the vehicle to a standstill via setting gearbox torque to zero is triggered. Therefore, the safety mechanism of the creep function is implemented by considering these conditions. After all these development processes, testing of specific driving test scenarios is simulated to check that if the plant model works as intended then specific functional safety fault injection test cases are simulated to see if the safe state which is defined based on safety goals works as intended to prevent severe accidents.
Diz ortezi giymiş insan kas iskelet örneği üzerinde derin pekiştirmeli öğrenmeyle yürüme öğrenmesi

(Lisansüstü Eğitim Enstitüsü, 2023) Kayan, Ömer ; Yalçın, Hülya ; 838669 ; Mekatronik Mühendisliği Ana Bilim Dalı

Günün olağan akışındaki işler, spor sırasındaki ani hareketler, kireçlenme veya yaşlanma nedeniyle insanlarda çeşitli sakatlanmalar meydana gelmektedir. Sakatlanmaların sınıflandırılması sonucunda diz, yaralanma sayısının en fazla olduğu ve iyileştirme giderlerinin en pahalı olduğu bölge olarak karşımıza çıkmaktadır. İnsan yapısının en büyük ve en karmaşık eklemi olan diz eklemi, üç önemli kemik (femur, tibia ve patella), dört çapraz bağ (iç, dış, ön çapraz ve arka çapraz), çok sayıda kas (kuadriseps, hamstringler, baldır kasları, gluteal kaslar ve popliteus), menisküsler (iç ve dış) ve kirişler (tendonlar) tarafından oluşturulmaktadır. Zaten karmaşık bir yapıya sahip olan diz eklemi bölgesi, sakatlanmalar sonrasında daha da karmaşık bir durum alabilmektedir. Yürüme sırasında kalçadaki kaslardan sonra en fazla erkeyi (enerji) dizdeki kasların tükettiği belirtilmektedir. Ayrıca diz eklemine vücut ağırlığının üç katına kadar yük bindiği belirtilmektedir. Diz ortezleri, eklemi dışarıdan desteklemek, eklemi korumak, biyomekanik dengeyi sağlamak, işlev bozukluklarını gidermek, ağrıyı azaltmak, zayıflamış kasları güçlendirmek amacıyla dizlerdeki sorunları iyileştirmeyi amaçlar. Ortezler genel olarak pasif ve aktif ortezler olarak iki sınıfa ayrılır. Pasif ortezlerde, hareketlilik ya önceden belirlenmiş aralıkların dışına çıkmaz ya da hiç hareket olmaz. Aktif ortezler ise üzerinde bulunan algılayıcılar ve eyleyiciler aracılığıyla hareket aralığını sürekli güncelleyerek insan bedenini daha verimli bir şekilde desteklemektedir. Her hasta öyküsü birbirinden farklı olduğu için bireysel iyileştirme yöntemi gerekir. Ortezler, her hastaya farklı şekilde takılarak ve ayarlanarak iyileştirme sürecine destek olur. Bu nedenle hastaya uygulanmadan önce, ortezlerin başarımlarının benzetim ortamlarında ölçülmesi, iyileştirme süreci boyunca verimliliği artırmaktadır. İnsan kas iskelet örneği benzetimleri, ortezin hastanın hareketlerini nasıl etkileyeceğinin önceden kestirilmesine olanak tanır.
Yinelemeli sinir ağları ile işaret dili tanıma

(Lisansüstü Eğitim Enstitüsü, 2023-01-27) Çetinkaya, İbrahim ; Ölmez, Tamer ; 518191015 ; Mekatronik Mühendisliği

İşaret dili sağır ve konuşma zorluğu olan bireylerin iletişim için kullandıkları dildir. Günümüzde işaret kullanımı fazla olmasına rağmen işaret dili öğrenmenin zorluğundan dolayı işaret dili bilen birey sayısı oldukça azdır. İşaret dili tanıma işaret dili öğrenme zorunluluğunu ortadan kaldırarak iletişimin arttırılmasını amaçlar. Ancak işaret dili tanıma zorlu bir problemdir. Çünkü işaretler el ve vücut hareketleri ve hatta yüz ifadeleriyle ifade edilir. Aynı zamanda işaretlerin birbirine benzemesi ve yapan kişiye göre farklılık göstermesi de işaret dili tanımanın zorlukları arasında sayılabilir. Son yıllarda özellikle derin öğrenme alanındaki çalışmalar artmıştır. GPUların da gelişmesiyle birlikte hesaplama gücü artmış bu da derin öğrenme alanındaki çalışmaların hızlanmasına yardımcı olmuştur. Günlük hayattaki birçok problemin çözümünde derin öğrenme kullanılmaktadır. İşaret dili tanıma problemini çözmek için de derin öğrenme algoritmaları kullanılmaktadır. İşaret dilini tanıma diğer insan ve bilgisayar etkileşimi için önemli olan bir diğer konu olan eylem tanımadan daha karmaşık bir konudur. Çünkü işaret dili anlatımının düzgün yapılabilmesi için el hareketleri ve mimiklerin daha açık bir şekilde ifade edilmesi gerekir. Literatürdeki bir çok çalışma işareti yapan kişiye ve işaretin yapıldığı ortama bağımlı olarak yapılmaktadır. İskelet anahtar noktalarının kullanımı bu bağımlılıkları tamamen ortadan kaldırmasada işaret dili tanımayı bu şartlara daha az bağımlı kılar. Bu çalışmada RGB videolardan elde edilen iskelet anahtar noktaları kullanılarak yinelemeli sinir ağları olan uzun kısa süreli bellek, kapılı tekrarlayan hücre modelleri kullanılarak işaret dili tanımlama amaçlanmıştır. İskelet anahtar noktaları sadece el ve kol üzerinden alınmış yüz ve vücut iskelet anahtar noktaları bu çalışmanın kapsamı dışında tutulmuştur. Her iki modelde zamana bağlı değişkenleri daha iyi modellemek adına iki yönlü olarak oluşturulmuştur. Aynı zamanda ezberleme ve gradyen kaybolması problemini çözmek adına düğüm seyreltme , katman normalizasyonu yöntemleri kullanılmıştır. Modellerin işaret dili tanımadaki performansları , GPU kullanım verileri ve hesaplama verimliliği karşılaştırılmıştır. Modelin performansı Türkçe işaret dili dataseti olan AUTSL üzerinde 50 işaret üzerinde denenmiş ve sonuçları paylaşılmıştır. Yapılan eğitimler sonucu Uzun kısa süreli bellek modelinin daha kısa sürede daha iyi doğruluğa ulaştığı görülmüştür. Ancak GPU kullanım değerlerine bakıldığına Kapılı Tekrarlayan Hücrenin daha düşük maliyetlerle çalıştığı gözlemlenmiştir.
Battery management system design with embedded electrochemical impedance spectroscopy

(Graduate School, 2023-04-27) Babacan, Medet Kerem ; Erol, Osman Kaan ; 518201019 ; Mechatronics Engineering

Humanity is developing day by day in engineering and technical fields. Engineers and scientists all over the world are trying to take humanity one step further. As a result of these studies, the technology provides comfort in our daily lives. One of the best examples of this are transportation, mobility and automotive. Each year, the studies progressing cumulatively in this field have pioneered the presentation of more developed cars than the previous years, and to populate different transportation methods and concepts in our lives. Each development has been formed as a result of some needs. One of the most important motivations in the field of automotive is user requests, the limited resources and the environmental sensitivity. The transition to electric vehicles, one of the biggest revolutions in transportation, has undoubtedly accelerated due to the depletion of fuel resources and the environmental sensitivity. Fuels used to operate internal combustion vehicles are obtained from petrol. While the formation of a petrol reserve takes for thousands of years, the current reserves are running out. Considering the demand that will rise in transportation due to the population and industrialization increase over time, it is predicted that the petrol reserves will be drained in the coming years. In addition, as a result of reactions inside the internal combustion engine, harmful gases are produced and released into world atmosphere. These gases, which are released from millions of vehicles, accumulate in the atmosphere and disrupt the balance of nature. Therefore, humanity has now become unable to lean on to petrol fuels and have been in search of new fuel sources. In this context, the most innovative transportation methods seem to be hydrogen and electrical based. While the comparison of these two methods with each other is the subject of a separate study, this study will focus on the electrical transportation method and the batteries to be used in these means of transportation. Transportation has been mainly provided by internal combustion vehicles until today. This naturally allowed many engineers working on this field to accumulate a lot of knowledge cumulatively. Over the years, engineers have solved the problems in the designs one by one and have reached the present knowledge level by pushing the limits of the existing technology. There have been many developments in internal combustion engines and vehicles in areas such as safety, efficiency, practicality and comfort. However, electric vehicles that have just started to become widespread have opened a new page. Compared to internal combustion propulsion systems, studies on electric propulsion systems are still in their infancy. Engineers and scientists are conducting a lot of work to fill the gap in this field. One of the most basic components of electric vehicles are batteries. When we compare one to one with internal combustion vehicle, the battery group corresponds to the fuel tank of the vehicle. The first factors for the user, such as the range of the electric vehicle, the charge time and the performance at different temperatures, are completely related to the battery. When these factors are examined, they are all disadvantaged xx compared to internal combustion vehicles. This offers a negative effect for the market share of electric vehicles. While the criterias mentioned are the factors that the user will experience directly, there is also a factor that the user cannot experience, but in fact, which is even more important than all of them, which is safety. As can be seen from time to time, electric vehicles may caught fire while charging or in a traffic accident. It is not possible to extinguish it when a battery flames. Therefore, this is a great danger for both the vehicle's user and for those around. These situations show that there are many more things to develop in terms of both safety and user experience in the batteries of electric vehicles. Today, Li-ion type cells are widely used in the batteries of electric vehicles. These cells are preferred because they are one of the cell types that give the highest energy per kilogram. As a result of chemical reactions in these cells, electrical energy is generated, which provides power to traction. Battery cells have safe operating ranges. In particular, the voltage and temperature values of the cells should be within some ranges. Otherwise, chemical reactions in the cells come to an uncontrollable point and undesirable fires, explosions or structural deformations may occur. In addition, since these cells are non linear systems, it is not easy to predict the changes in their internal structures as a result of their use. For this reason, it is a research area in itself to predict the energy remaining in the battery of an electric vehicle and therefore the range it can go to. In order to overcome such difficulties, there is a control unit that manages the battery and this module is called the battery management system. In this study, a battery management system will be developed to ensure the safety of the electric vehicle battery and has a new method to estimate the chemical structure of the batteries. The developed battery management system will measure voltage, current and temperature values in the battery and check whether the battery is at safe ranges. It will take the necessary actions to prevent these values get dangerous. In addition, the battery will drive auxiliary elements in battery pack such as contactors. It will send the measurements and calculations taken over the battery over the communication channels and work in harmony with the other components in the vehicle. The designed battery management system will be scalable and the big battery packets will be able to managed with different number of battery management system modules. There are many methods to analyze the chemical structures of batteries. The most important of these is electrochemical impedance spectroscopy. In this method, an alternative current is sent to a battery cell in the laboratory environment and the voltage change in the cell terminals is monitored. This voltage change analyzed in the frequency domain and an idea is obtained about the chemical internal structure of the cell. In spite of obtaining valuable information as a result of this method, the devices that do this analysis are expensive, heavy and stationary devices that can be used only in the laboratory environment. Within the scope of this study, it is aimed to integrate such an analysis method into designed battery management system. Thus, the tests performed in the laboratory will be able to performed on the vehicle also, and the accuracy will increase for battery management system calculations. Within the scope of this study, the hardware of a battery management system will be developed. After circuit schematic and printing circuit board design completed, circuit board will be produced and prototyping work will be done. Low level drivers, battery management system algorithms and electrochemical impedance analysis algorithms will be developed on this board. The developed product will be tested on a battery pack and measurements will be taken. Taken measurements will be used to express cell structure as an equivalent circuit model. Application areas that product can be used and future studies will be discussed.
Electrified powertrain simulation and validation of a fuel cell electric vehicle

(Graduate School, 2023-06-23) Akar, Burak ; Yalçın, Hülya ; 518191039 ; Mechatronics Engineering

In this study, electrified powertrain simulation of a fuel cell electric vehicle and the verification of its outputs with experimental data was focused. The validation study was provided with the test data of the Toyota Mirai (2017) vehicle published by Argonne National Laboratory. Rapid population growth brings with it increasing urbanization and industrialization. As a result of this, the harmful effects observed on our ecosystem due to human-induced effects are becoming more and more evident. Rising average global temperatures and air pollution are among its most important direct consequences. Various regulations and strategic targets have been established by the United Nations and its sub-organizations to control the negative results of human-induced activities directly or indirectly and for a sustainable future. As a result, increasingly stringent emissions targets in the field of transportation can be shown. The acceleration of this transformation and emission targets increases as the suitability and applicability of the technology is ensured. Battery electric vehicles, hybrid electric vehicles, and fuel cell electric vehicles are increasingly coming to the fore in meeting these targets. Electric vehicles stand out not only as a solution to environmental problems but also with their high performance and efficiency features. Battery electric vehicles belonging to the electric vehicle ecosystem are the most common and simplest structure. They provide the necessary energy from a high-voltage battery and have an electric motor for traction. Hybrid electric vehicles, on the other hand, have an internal combustion engine besides electric motor, unlike battery electric vehicles. They can work in many different paradigms depending on the intended use. Fuel cell electric vehicles provide their energy from the fuel cell and battery system with various energy management system algorithms. In this study, Toyota Mirai(2017), which is a fuel cell electric vehicle that provides its main power with the fuel cell system, was chosen. The power required by the vehicle is provided by low-voltage or high-voltage buses. In the vehicle, auxiliary devices are supplied with low voltage directly from the battery. On the other hand, while high voltage components are mainly fed by the fuel cell system, the battery can also be fed according to the energy management strategy. The system also includes DC/DC converters to change the voltage level and an inverter to supply this generated DC to the AC electric motor. The forward approach methodology is used to perform the drive cycle simulations. This method is used because it gives more accurate results and offers a more realistic approach than the other method (backward approach). This approach requires a driver model. In order to achieve this, a PI controller is used to keep the speed of the vehicle at the reference speed level in the simulation. This controller gives acceleration or braking commands just like a real driver. It calculates the required torque by taking into account the vehicle loads obtained by using the coast-down coefficients and demands it from the electric motor. Thus, the electric motor operates at a certain operating point. This operating point corresponds to a point in the contoured efficiency map of the electric motor. The calculated total electrical power is requested between the fuel cell and the battery system with a rule-based controller according to the energy management strategy. This controller has been developed based on the requested power amount and SoC level by examining the tests conducted by the Argonne National Laboratory. The Rint battery equivalent circuit model is used to calculate the resistance, current, voltage, and charge state of the high-voltage battery. The Nernst voltage is calculated to obtain the maximum theoretical cell voltage of the fuel cell stack. Then the activation, ohmic, and concentration losses are calculated. By subtracting these losses from the Nernst voltage, the polarization curve is obtained. Using ideal gas equations, the gas flow is modeled depending on the partial pressures in the manifold. With these equations, the partial pressures of nitrogen, oxygen, and water vapor in the cathode volume are calculated. An equation is used between the utilized substance and the current. Thus a relation is established between reactants and current. Similarly, an equation is used for the amount of utilized hydrogen for the anode part. In addition, the liquid water formed in the cathode volume is calculated according to the relative humidity. The required amount of air required by the system is provided with the help of a compressor. The fuel cell system response delay is modeled using a low-pass filter. Finally, the temperature changes of the system components are monitored by establishing the heat balance equation throughout the simulation. The instantaneous acceleration of the vehicle is calculated using Newton's second equation of motion. Net force is obtained by subtracting resistive forces which slows the vehicle from the forces that provides traction. Using vehicle mass and net force instantaneous acceleration is found. The instantaneous velocity is found by integrating this value. Extensive reports and raw test data published by Argonne National Laboratory were reviewed to validate the simulation outputs. First, the characteristic curve of the fuel cell system, the stack and system efficiencies according to the power it provides, and the reactant consumptions are compared. The results were considered to have an appropriate accuracy. Then, in order to examine the characteristic delay response of the fuel cell system, instantaneous power requests and power cuts were examined in the simulation as well as in the test data. Later, the maximum power test conditions were established in the simulation environment to evaluate the response of the vehicle's fuel cell system, battery, and electric motor at high loads. When both simulation and test results were examined, it was observed that it could supply 110kW for 30 seconds and then 75kW continuously. Since the maximum power test was also carried out with full power at 25% grade level, at the same time, gradeability analyses of the vehicle could be made with these data. Accordingly, when the vehicle speed is examined in the test data, it is observed that the highest speed value is 72.5 km/h and it can reach 44 km/h continuously. On the other hand, when the same conditions were repeated in the simulation environment, the highest speed and the speed it could reach continuously were obtained as 79 km/h and 48.4 km/h, respectively. When the vehicle's acceleration of 0-80 mi/h on flat ground was examined, it is seen that it reaches 16.7s both in the test and in the simulation. However, when the acceleration of 0-100 km/h is examined, the target speed was reached in 8.9s in the simulation environment, while this value was measured as 9.6s in the tests. Last but not least, Steady State Speed, WLTP and UDDS driving cycles were compared in detail with many data test outputs related to the electric motor, fuel cell system and battery, and the results were evaluated. The comparisons were generally found to be quite satisfactory in terms of simulation reliability and matched significantly. Observed deviations are explained in detail. One of the unexpected findings was that during every driving cycle the vehicle demanded power from the fuel cell system even though it did not need it for traction. It has been observed that this power charges the battery regardless of the state of charge level. When the hydrogen consumption in the test is examined; while the consumption was measured as 192.6g in the test data in the WLTP driving cycle, it was calculated as 190.3g in the simulation. Similarly, this evaluation was made for the UDDS driving cycle, the measurement result obtained in the test was 75.7g, while the consumption calculated in the simulation was 75.1g. Accordingly, the error was found to be 1.19% and 0.80%, respectively.
Dynamic model-based path planning optimization and control for USV in inland waterways

(Graduate School, 2023-07-10) Büyükçolak, Ferhan ; Tayyar, Gökhan Tansel ; 518201013 ; Mechatronics Engineering

The aim of this thesis study is to apply the Guidance, Navigation, and Control (GNC) system for autonomous marine technology to a marine vehicle in the form of a catamaran with a differential drive system. The Model Predictive Controller (MPC), which is a model-based control approach, is used for controlling the system. Within the scope of the study, a simulator including the dynamic model of Otter USV, a vehicle owned by Maritime Robotic AS company, has been utilized. Firstly, within the scope of the study, the system model of the used vehicle has been defined, and the components of the vehicle's mathematical model have been described. In order to use it in the model-based controller, a system identification approach has been employed to determine the coefficients of the vehicle's mathematical model. For system identification, various maneuvers were performed on the vehicle's simulator model, and navigation data was collected. Using this collected navigation data, the values of the parameters of the vehicle's dynamic model were determined through the non-linear least square method. Secondly, the development of the guidance system for the vehicle has been carried out. A system has been developed that can reach the target point while avoiding collisions in an environment with static obstacles, taking into account all input and differential constraints of the vessel model. For global path planning, a method called Kinodynamic RRT has been developed, which plans the path by considering the dynamics of the vehicle. In addition, utilizing the optimal control problem approach, an optimization-baed path planning has been performed. To enable the vehicle to follow the generated overall path, the implementation of a path following algorithm called Line of Sight (LOS) has been applied to this system. In this study, since the focus was on the realization of vehicle trajectory tracking in narrow waterways, different approaches were taken in the calculation of the lookahead distance in this method to improve the performance of the classical LOS method. The following of the generated path by the guidance system of the vehicle and the following of the reference state values generated for path following have been performed using a nonlinear model predictive control (NMPC) system. To find the optimum values of the parameters that affect the performance of the controller, the performance of the controller has been tested in different scenarios, and the most suitable values have been determined. In order to create this model-based controller and to have a suitable software architecture for real-time requirements, a fast solution method was needed, so the algorithm was developed in the CasADi optimization framework. To observe the performance difference between the developed controller and conventional control methods, a suitable PID controller has been developed for the Otter USV. The performance of these two controllers has been compared in scenarios with and without disturbances.
Addressing parametric uncertainties in autonomous cargo ship heading control

(Graduate School, 2023-07-13) Jambak, Ahmet Irham ; Bayezit, İsmail ; 518211022 ; Mechatronics Engineering

The progress of computer technology has had a profound influence on the maritime sector, particularly in relation to ship autonomy. The incorporation of computer-assisted systems for guidance, navigation, and control has emerged as a promising approach to minimize the potential risks associated with human errors during ship maneuvering. These errors have the potential to lead to disastrous consequences such as collisions with obstacles, vessel damage, and endangering the safety of passengers and cargo. Several notable studies have explored ship control systems using different control approaches and conducting simulation-based and real-time implementation tests. These studies include adaptive path following control for accurate target tracking, stabilization of heading angle using cascade control simulations and fuzzy logic-based decision-making mechanisms, integration of sensor information to reduce accidents on common ship routes, collision scenario analysis with fuzzy control-based decision-making aligned with international maritime regulations, design and analysis of planar autonomous position control using two independent propellers, rudder, speed, and position control experiments on a catamaran prototype using a PID approach enhanced by a Kalman Filter, and modeling and real-time control of unmanned surface vehicles with accurate parameter identification. These studies have provided valuable insights and advancements in ship control systems. Extensive research has also been carried out to address the control of ships with uncertain hydrodynamic coefficients, resulting in the exploration of various approaches. One approach involves using a Multi-level Model Predictive Control (MPC) method to regulate ship speed and calculate propulsion energy while considering uncertainties. Another approach is adaptive control, which continuously adjusts control inputs based on real-time measurements of ship behavior. Fuzzy logic-based control is also utilized, incorporating fuzzy rules that account for uncertainty in hydrodynamic coefficients to adapt the ship's control inputs. Machine learning techniques, like reinforcement learning, are employed to adjust control inputs based on available data. Additionally, robust control techniques are developed to ensure stable and predictable ship behavior even when faced with uncertain hydrodynamic coefficients. These studies make valuable contributions to ship motion control by addressing the challenges associated with uncertain hydrodynamic coefficients and proposing effective control strategies. This thesis aims to address two significant aspects in the field of ship control. First, the development of a comprehensive ship motion model for the ship's heading angle. Second, the effective handling of parametric uncertainty in ship hydrodynamics. The research focuses on enhancing the understanding of ship behavior and designing control strategies that can robustly handle uncertainties, ultimately improving the performance, safety, and efficiency of ship operations. The first objective of this thesis is to construct a control-oriented ship motion model that accurately represents the ship's heading angle dynamics. The model incorporates both linear and nonlinear dynamics to account for the complexities of ship motion under various operating conditions. To derive the linear model, certain assumptions are made to simplify the typical six degrees of freedom (6DOF) equation of motion into a three degrees of freedom (3DOF) equation. From a motion perspective, slow-speed displacement vessels exhibit minimal heave, roll, and pitch motions. Therefore, the variables $Z$, $K$, $M$, and their derivatives, along with the angular velocities $w$, $p$, $q$, can be neglected. From a geometric perspective, conventional ships are symmetrical on the $xz$-plane. As a result, it is assumed that the $y$-coordinate of the ship's center of gravity is zero $y_G = 0$. For the nonlinear model, a well-established 3DOF ship model provided by the Manevering Modelling Group (MMG) is utilized. This model extends the previously derived control-oriented ship equation of motion by incorporating the dynamics of the ship's propeller. By integrating the propeller dynamics into the model, a more comprehensive understanding of the ship's behavior and the interaction between its motion and the propeller can be achieved. The derivations and explanations in this subsection aim to provide valuable insights into the nonlinear ship equation of motion with propeller dynamics, serving as a useful tool for ship motion control design and optimization. By establishing a reliable ship motion model, it becomes possible to design effective control strategies for heading angle control. This aspect of the research involves reviewing and analyzing existing studies on ship autopilot design, including control methods such as adaptive path following controllers and cascade control simulations. In order to validate the model's accuracy, a turning circle test was conducted. This validation process done by comparing the model's predictions with experimental data from previous studies. To ensure a reliable validation process, a 1/80 scale model of the DTC Container ship was chosen for physical validation. The study's results convincingly demonstrate the model's ability to accurately approximate the trajectory with a fixed rudder angle of $\delta = 35$ degrees. Both the linear and nonlinear models developed in this study exhibit a high level of agreement with the actual system, comparable to the results obtained from other studies utilizing CFD and system-based approaches. The second objective of this thesis is to address the challenge of parametric uncertainty in ship hydrodynamics, particularly focusing on the uncertainty associated with hydrodynamic coefficients. Hydrodynamic coefficients play a crucial role in understanding the interactions between the ship and the surrounding water. However, these coefficients often exhibit variations due to various factors, such as environmental conditions, vessel modifications, or manufacturing tolerances. The presence of such uncertainty can significantly impact the performance and reliability of ship control systems. To address this issue, optimization techniques such as Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) have been used to determine the optimal coefficients that best match the ship's motion. However, these methods can be slow, particularly if a large number of samples are needed to represent the uncertainties in the hydrodynamic coefficients. To answer this challenge, this thesis designed a fast optimization algorithm to find a robust optimal controller for ship heading angle control with a certain level of error in hydrodynamic coefficients that is difficult to solve deterministically. The proposed optimization algorithm is referred to as "Bisection Optimization via Blind Search". This methodology involves simulating the model for a total of $n$ samples, utilizing $m$ randomly sampled controller parameters $K$. The resulting cost value $\omega$ is recorded for each simulation. Subsequently, the controller parameter $K$ that produces the lowest $\omega$ value is selected. In the second stage, a bisection-based optimization technique is employed to further refine the chosen controller parameter $K$. In this thesis, the uncertainty levels considered in this study are set at $\pm$20$\%$, representing the permissible deviations of parameters from their nominal values. To mitigate the adverse effects of uncertainty, a simulation scenario is created where the controller is tasked with adjusting the yaw angle $\psi$ from 0 degrees to 40 degrees. To evaluate the optimization performance, four different cost functions are employed: Integral Absolute Error (IAE), Integral Squared Error (ISE), Integral Time Absolute Error (ITAE), and Integral Time Squared Error (ITSE). However, the results indicate that the optimal controller parameters obtained using these different cost functions do not exhibit significant differences. Two types of controllers, namely proportional (P) and proportional-derivative (PD) controllers, are investigated in this study. The inclusion of the derivative term in the PD controller aims to mitigate oscillations and overshoot in the system's response, thereby improving stability and settling time. However, the integral term is excluded from consideration due to the inherent stability of the system and its expected slow response. The results demonstrate that the proposed algorithm outperforms existing methods such as Particle Swarm Optimization (PSO) in terms of both execution speed and task performance. By achieving these 2 objectives, this thesis contributes to the field of ship control by providing a comprehensive understanding of ship motion dynamics and offering effective solutions for addressing parametric uncertainty in ship hydrodynamics. The outcomes of this research can significantly impact various maritime applications, including autonomous navigation, collision avoidance, and energy-efficient ship operations. The developed ship motion model and the proposed optimization approaches can be implemented in real-world scenarios, enabling improved control strategies for ship heading angle control and enhancing the overall performance and safety of ship operations. In conclusion, this thesis combines the development of a control-oriented ship motion model with the effective handling of parametric uncertainty in ship hydrodynamics. The research contributes to the advancement of ship control by providing valuable insights, methodologies, and tools that can be utilized in designing robust control strategies for ship heading angle control under uncertain operating conditions. The findings of this thesis have the potential to enhance the efficiency, safety, and sustainability of ship operations, ultimately benefiting the maritime industry as a whole.
Quadrotor dinamik modelinin ve kontrolcüsünün freertos işletim sistemi ile Raspberry Pi üzerinde gerçeklenmesi

(Lisansüstü Eğitim Enstitüsü, 2023-07-14) Büyükçolak, Ömer Serhat ; Yeniçeri, Ramazan ; 518191026 ; Mekatronik Mühendisliği

Bu tez çalışmasında bir Quadrotor'un matematiksel modellenmesi ve irtifa kontrolü Matlab ortamında yapılmış, benzetim C programı olarak çalıştırılmıştır. C programına dönüştürülen benzetim, Raspberry Pi geliştirici kartları üzerinde FreeRTOS işletim sistemi içerisinde yüksek önceliğe sahip bir görev olarak çalıştırılmıştır. Çalışma kapsamında Quadrotor aracı, matematiksel olarak modellenmiş ve sistem denklemleri için tüm kuvvet ve tork eşitlikleri türetilmiştir. Gerçeklenen benzetim senaryosu için varsayımlar tanımlanmış ve model ilk olarak sadeleştirilmiştir. Klasik bir PD kontrol stratejisi ile aracın irtifa kontrolü yapılmıştır. Kontrolcünün çalışması farklı referans seviyeleri ile test edilmiş ve çıktılar yorumlanmıştır. Matlabda gerçeklenen senaryo, C dili ile ayrı bir program olarak gerçeklenmiştir. Gerçek zamanlı işletim sistemine geçmeden önce, benzetim, C programlama dili ile dış kütüphane bağımlılığı olmaksızın gerçeklenmiştir. Buı sayede, C dili ile geliştirilmiş programları çalıştırabilen her donanım üzerine bu benzetim taşınabilir hale gelmiştir. Gerçek zamanlı işletim sistemi alternatifleri kullanılacak geliştirme kartları göz önünde bulundurularak deperlendirilmiştir. Raspberry kartlarından, Pi Zero ve Pi 4 isimli iki adet geliştirme kartı kullanılmıştır. Gerçek zamanlı işletim sistemi olarak FreeRTOS kullanılmaya karar verilmiştir. Resmi olarak Raspberry Pi için FreeRTOS desteklenmese bile, aynı işlemci ailesinden bir işlemciye sahip başka kartlarda çalışabildiğinden, düzgün taşıma işlemi yapıldıntan sonra her iki kart üzerinde de çalıştırılmıştır. Benzetim programı için, iki farklı benzetim sistem tasarımı önerilmiştir. İlk tasarım, tüm benzetim programını sadece Pi Zero kartı üzerinde çalıştıracak ve sonuçları analiz bilgisayarına gönderecek tek kartlı bir tasarımdır. Bu tasarım için, benzetim çıktıları, Matlab benzetimi ile aynı çıktıları üretmiştir. Zamanlama analizinde, tek kartlı tasarım önerisinin kabul edilebilir bir hızda çalıştığı gözlemlenmiştir. Gerçek quadrotor için Pi Zero kartı, FreeRTOS ile birlikte kullanıma uygun olduğu görülmüştür. İkinci tasarım, benzetim programını iki ana döngüye bölerek, iki farklı kart üzerinde gerçekler. Benzetim senaryosunda model dinamikleri Pi Zero üzerinde, kontrolcü ise Pi 4 üzerinde gerçeklenmiş ve iki kart arası haberleşme seriport bağlantı kanalı ile gerçeklenmiştir. Benzetim sonuçları, ilk tasarım ve model ile birebir aynı olsa da, zamanlama incelendiğinde ikinci tasarımın çok kötü performans sergilediği gözlemlemiştir. Tasarımdaki problem incelendiğinde, sorunun kaynağı seriport olarak belirlenmiştir. Kartlar yoğun veri transferi olduğundan, bu haliyle seriportu direkt olarak kullanmak, beklenenin altında sonuç vermiştir. Gerçek quadrotor gerçeklemesinde, iki kartlı tasarımın kullanılması önerilmemektedir.
Model reference adaptive controller design with augmented error method for lane tracking

(Graduate School, 2023-11-20) Diyici, Mehmet Nuri ; Yalçın, Yaprak ; 518201038 ; Mechatronics Engineering

At the beginning of the automobile industry history, automobiles were simple mechanical systems. Starting from Ferdinand Verbiest's steam-powered vehicle in 1672, called a toy, automobiles have evolved into complex machines. Essential inventions, such as the design of the first internal combustion-powered vehicle by François Isaac de Rivaz in 1808 and the gasoline-powered automobile by Karl Friedrich Benz in 1886, automobiles became available for everyday use. Especially the introduction of the Ford Model T by the Ford Motor Company in 1908, which was the first mass-produced commercial automobile, automobiles became common on roads. Thus, the safety and riding comfort specifications became significant factors for automobile producers in the automobile industry. In the early 20th century, the pace of evolution increased dramatically thanks to the computerization and electronics in automobiles, which led to the introduction of Electronic Control Units (ECUs) and onboard computers, allowing for more precise control over engine performance and emissions and vehicle stability. Moreover, these computers and electrical components were used to design driver assistance systems introduced for driving comfort and safety during the 20th century. The initial features, such as anti-lock braking system (ABS) and cruise control (CC), were worked effectively. Later, these features were improved, advanced, and varied for different purposes under autonomous driving. Recently, the automotive industry has undergone a distinctive transformation towards autonomy, which governments and leading companies like Tesla and Google support. Advanced driver assistance systems (ADAS) play a crucial role in autonomous driving. ADAS includes features implemented in vehicles to enhance safety and riding comfort by improving user awareness and controlling vehicle movement. Driver support systems can be categorized from various perspectives, including active, passive, safety, and comfort. Active driver assistance systems assume control of certain vehicle functions, while passive control systems warn the driver. According to the vehicle control point of view, ADAS is covered under two main categories: longitudinal and lateral motion control. Features like ACC and AEBS, for example, are associated with controlling the longitudinal motion of a vehicle, primarily focusing on speed and distance management. On the other hand, LKA/LCA and BSD features are within the domain of lateral motion control, mainly concerned with maintaining proper alignment within a lane and detecting vehicles in adjacent blind spots. Within the scope of this study, an adaptive controller is designed for lane tracking of autonomous vehicles. The controller algorithm aims to center the vehicle on the lane by calculating the required front steering angle. The controller's performance is simulated and evaluated, and finally, further tasks are determined. Lane tracking control design is handled either with a model-free or a model-based approach in the literature. Model-free methods provide an alternative option when creating models becomes inaccurate and challenging. These control strategies typically rely on data-driven techniques such as supervised learning, reinforcement learning, and fuzzy logic control. Model-based approaches, such as MPC, SMC, LQR, and $H_\infty$, on the other hand, use the mathematical representation of the vehicle's lateral motion, which plays a significant role in controller design. Simulation of the vehicle system using this representation provides a clear perspective for the evaluation of designed controller performance and calibration. Vehicle models for lane tracking controller design are categorized within various aspects. While the mathematical representation of a vehicle, whether it is linear or non-linear, is in one category, its configuration type is the second one. Three vehicle model configuration types are available in the literature: geometric, kinematic, and dynamic vehicle models. Each of these configuration types has advantages and disadvantages that must be considered while designing a controller. The bicycle dynamic vehicle model is the popular representation used in this thesis. Lateral path error is derived as the function of vehicle lateral motion state variables (lateral, longitudinal velocity, and yaw angle of the vehicle) on the ego lane, which is the output of the control system according to the bicycle model. Then, this derived model is used to determine the adaptive control law to achieve the desired tracking performance. The adaptive control method is one of the most promising methods to create reliable solutions to the difficulties faced by autonomous vehicles in lane tracking. Although different types of adaptive control design methods are available in the literature, model reference adaptive control (MRAC) is the most suitable in terms of clarity and low computational burden, as well as real-time application. In this thesis, it is clearly seen that the derived vehicle model is a perfect fit for the adaptation of feedforward gain with the output feedback based on the passivity. However, due to that the derived model's transfer function, based on the parameters of an autonomous large-size vehicle, is not SPR makes the model unsuitable for model reference adaptive controller design. As a solution, the augmented error method is used to enable the application of the passivity approach to determine the adjustment rules of controller parameters. Thus, the controller design, which ensures the input-output stability with MRAC, is derived based on the augmented error method. As a result, it is seen that the model reference adaptive controller system with augmented error method showed a perfect tracking performance according to the simulations on Simulink. Considering similar studies, the control signal obtained in the simulation showed that the model is applicable for real-time application.

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