Sürdürülebilir Kalkınma Amaçları
Yayınlar
- MakaleAçık Erişim2018Scopus SJRQ3Design, analysis, and control of in-wheel switched reluctance motor for electric vehicles
Omaç, Z.; Polat, M.; Öksüztepe, E.; Yıldırım, M.; Yakut, O.; Eren, H.; Kaya, M.; Kürüm, H.
Estimation of dimension parameters for an electric machine has great importance before assembling on production line. As a matter of fact, researchers should find optimum solution once they decide to perform analytical design of an electric machine. In this study, we have tried to find dimensional and electrical parameters via derived mathematical equations for in-wheel switched reluctance motor (IW-SRM), and the motor has been manufactured. Moreover, an experimental setup is designed, and the speed and torque control of IW-SRM is carried out. The motor tests including both standstill and running test are performed by using the experimental setup. Initial size parameters are intuitively provided as motor analysis is conducted by software package. Then, numerous trials are examined to get optimum results. In fact, this motor is employed by an electric vehicle whose design is ongoing. Therefore, optimum motor parameters for required base speed and torque have been estimated by solving generated equations for IW-SRM with 18/12 poles via MATLAB. Considering parameters estimated, analysis of IW-SRM has been performed by Ansoft Maxwell 15.0 Software Package based on 3D finite element method (3D-FEM). Consequently, the estimated parameters have been validated by the results of Maxwell 3D FEM. Experimental results of the motor manufactured are obtained via the motor driver designed; also have been validated by Maxwell 3D.
AtıfScopus14WoS15OpenAlex24
İncele - BildiriYalnız künye2014DESIGNING IN-WHEEL SWITCHED RELUCTANCE MOTOR FOR ELECTRIC VEHICLES
Yildirim, M.; Polat, M.; Öksüztepe, E.; Omaç, Z.; Yakut, O.; Eren, H.; Kaya, M.; Kürüm, H.
Estimation of dimension parameters for an electrical machine has great importance before manufacturing. For this reason, analytical design should be performed in an optimum form. While motor analysis is accomplished by package programs, initial size parameters are intutivily provided and then various trials are examined to get optimum results. In this study, we are trying to find dimensional and electrical parameters generating mathematical equations in analytic approaches for In-Wheel Switched Reluctance Motor (IW-SRM), which will be employed by Electric Vehicle (EV). Therefore, optimum motor parameters for required speed and torque have been estimated by solving generated equations for in-wheel SRM with 18/12 poles via MATLAB. Using the parameters, analysis of in-wheel SRM has been carried out 3D Finite Element Method (FEM) by Ansoft Maxwell 15.0 Package Software. Consequently, the accuracy of the estimated parameters has been validated by the results of Maxwell 3D FEM.
AtıfWoS10İncele - BildiriYalnız künye2014Estimation of Confidence Regions and Severity of Undefined Faults in Driving using Synthetic Disturbance Signals
Yakut, O.; Eren, H.; Kaya, M.; Oksuztepe, E.; Polat, M.; Omac, Z.; Kurum, H.; Celenk, M.
In this study, we aim to determine fault severity in an electric car that may be caused by yawing due to such disturbances as non-uniform road pavements, in-wheel bearing clearance, suspension system, driver under Influence of alcohol (DUI), and tire deformation. The major research contribution herein is to alert drivers about an unforeseen situation on steering wheel whether it refers to a severe fault or contemporary states. In a sense, the undertaken study serves as a state of the art driving assistant system operating under unsteady conditions. We determine the fault severity of the system via classifying it into specified confidence regions by estimating the deviation from a monotonous straight route for any unstable situation. In this way, the proposed system informs driver to gain an insight about the severity level of arising problematic scenario. In order to realize the classification of confidence regions, we initially obtain the overall dynamic model of the system. Then, disturbance functions with different amplitudes and frequencies are characterized and included in the dynamic system specification. Here, the confidence regions have been constructed as to respective fault severity level of the car through the system response. Trajectory of vehicle in dynamic driving conditions considering these perturbations and noises are interrelated through the Kalman filtering to predict deviations from the desired trajectory and the prediction error. In simulation scenarios, Dynamic Time Warping (DTW) is employed to obtain deviation from ground truth under different noise functions, and results are sketched graphically assigning rate of fault severity into specified confidence regions. Initially, we have modeled the proposed system considering an electric car although the idea can readily be generalized for all cars with four tires. Presently, fault severity with classified confidence regions has been investigated under a simple car model.
- MakaleYalnız künye2013Dynamic Risk Modeling for Safe Car Parking in Climbing over Urban Curbs
Yakut, O.; Eren, H.; Kaya, M.; Oksuztepe, E.; Polat, M.; Omac, Z.; Bekler, D.; Kurum, H.; Celenk, M.