Browsing by Author "Bulent Ertan,H."
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Editorial Citation Count: 0ACEMP-OPTIM 2019 Opening Speech(Institute of Electrical and Electronics Engineers Inc., 2019) Ertan, Hulusi Bülent; Electrical-Electronics Engineering[No abstract available]Conference Object Citation Count: 0An approach for Improving Performance of Sensorless Field Control(Institute of Electrical and Electronics Engineers Inc., 2018) Ertan, Hulusi Bülent; Filci,T.; Electrical-Electronics EngineeringSensorless vector control is preferred in some applications, because there is no need for speed or position sensor. However, by their very nature, they are susceptible to making position error in rotor position estimation. As a consequence the performance of motor drives employing this technology is lower than those which employ sensors. This paper presents a new approach which identifies and uses rotor slot harmonic current component in the stator current to identify rotor position. The time taken by the algorithm used is short enough to be embedded within the vector control algorithm. The essence of the algorithm is treating the current component due to rotor slot harmonics as an amplitude modulated signal on the fundamental current component. The magnitude of this current component is identified via demodulation. Using this information rotor position and speed can be determined. This approach is tested on a commercial induction motor and some results are presented which illustrate that rotor position can be successfully determined. © 2018 IEEE.Conference Object Citation Count: 0An approach for Improving Performance of Sensorless Field Control(Institute of Electrical and Electronics Engineers Inc., 2018) Ertan, Hulusi Bülent; Bulent Ertan,H.; Filci,T.; Electrical-Electronics EngineeringSensorless vector control is preferred in some applications, because there is no need for speed or position sensor. However, by their very nature, they are susceptible to making position error in rotor position estimation. As a consequence the performance of motor drives employing this technology is lower than those which employ sensors. This paper presents a new approach which identifies and uses rotor slot harmonic current component in the stator current to identify rotor position. The time taken by the algorithm used is short enough to be embedded within the vector control algorithm. The essence of the algorithm is treating the current component due to rotor slot harmonics as an amplitude modulated signal on the fundamental current component. The magnitude of this current component is identified via demodulation. Using this information rotor position and speed can be determined. This approach is tested on a commercial induction motor and some results are presented which illustrate that rotor position can be successfully determined. © 2018 IEEE.Conference Object Citation Count: 5Integration of Offshore Wind Farm Plants to the Power Grid using an HVDC line Transmission(Institute of Electrical and Electronics Engineers Inc., 2019) Ertan, Hulusi Bülent; Pourkeivannour,S.; Negadi,K.; Boumediene,B.; Allaoui,T.; Bulent Ertan,H.; Electrical-Electronics EngineeringThis paper investigates an integration of Offshore Wind Farm Plants with Power Grid Based on an HVDC line Interconnection. Large offshore wind farms are installed in the North Sea area using modern multi-megawatt wind turbines. The Voltage source converter-high voltage direct current VSC-HVDC is a suitable means of integrating such large and distant offshore Wind Power Plants (WPP) which need long submarine cable transmission to the onshore grid. The offshore network then becomes very different from the conventional grid, in that it is only connected to electronic power converters. A wind farm model with VSC-HVDC connection is developed. This work presents the modeling and simulation of such a system. The dynamic study of system performance under the fluctuations of wind energy and wind speed was studied to demonstrate the effectiveness of the control strategy. The validity of the proposed control technique is verified by Matlab/Simulink. Simulation results presented in this paper confirm the validity and feasibility of the proposed control approach, and can be tested on experimental setup. © 2019 IEEE.Conference Object Citation Count: 0Rotor Resistance Estimation of Induction Motors with A Novel Innovation-Based Adaptive Extended Kalman Filter for Self-Tuning(Transilvania University of Brasov 1, 2023) Ertan, Hulusi Bülent; Bulent Ertan,H.; Electrical-Electronics EngineeringIn this study a novel estimator is developed to identify the rotor resistance of the induction motor (IM) at standstill for self-tuning. For this purpose, an innovation-based adaptive extended Kalman (IAEKF) filter estimator is designed. IAEKF provides a more dynamic estimation compared to the conventional extended Kalman filter (EKF), as they have a mechanism where the system noise covariance matrix can be updated continuously, unlike conventional EKF. To increase estimation stability and also for position and amplitude information of the motor flux required for the dynamic control methods, stator stationary axis (-αβ) components of stator current and -αβ components of stator flux are estimated with rotor resistance by using the correlation between states and parameters defined as nonlinear inputs. The estimation performance of the proposed IAEKF algorithm is tested both in the simulation and on the real-time IM experimental setup at standstill. Simulation and real-time results show that the estimation achievement of the proposed IAEKF algorithm is quite impressive. © 2023 IEEE.Conference Object Citation Count: 3Standstill Estimation of Stator Resistance of Induction Motors with Novel Innovation-Based Adaptive Extended Kalman Filter(Institute of Electrical and Electronics Engineers Inc., 2021) Ertan, Hulusi Bülent; Yirtar,M.Z.; Bulent Ertan,H.; Electrical-Electronics EngineeringIn this study, a method is developed to identify stator resistance of an induction motor (IM) at standstill in the self-tuning. An innovation-based adaptive extended Kalman filter (IAEKF) estimator in which the process noise is dynamically updated with an adaptive mechanism different from the conventional extended Kalman filter (EKF) is designed to estimate stator resistance with αβ- stator stationary axis components of stator current and αβ- components of stator flux of an IM. The reason for estimating the stator flux and stator current together with the stator resistance is to both increase the stability of the proposed estimator algorithm by using the correlation between the parameters and states in the non-linear inputs applied to the estimator and obtain the motor flux information needed by the control system. In the proposed IAEKF algorithm, a stator flux-based IM model is used for prediction purposes. The standstill estimation performance of the proposed novel IAEKF is tested with both sinusoidal and PWM power supplies, The real-time estimation results show the effectiveness and prediction accuracy of the proposed stochastic-based estimator. © 2021 IEEE.