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Colloquium
July 24 @ 3:00 PM - 5:00 PM IST
Date/Time: Jul 24 / 15:00:00
Location: Multi Media Class Room (MMCR), EE Department
Research Supervisor: Narayanan G
Abstract:
Switched reluctance machine (SRM) is known for many advantages such as permanent magnet-free operation, robust structure, low rotor inertia, low manufacturing cost, and excellent fault-tolerant capability. Hence, SRM has been adopted in many applications such as, electric vehicles, aerospace, and robotics. Nonlinear characteristics and pulsations in torque developed are well-known problems, rendering modelling and control of the SRM challenging. Hence this thesis focuses on the modelling, analysis and control of switched reluctance machines. Current, torque and speed control are all part of the scope of study. Conventionally rotors with laminations are used in SRM. However, in applications where shaft temperatures are very high, rotors made from a single piece of magnetic material are potential candidates. Solid-rotor and recently proposed slitted-rotor SRMs are prospective candidates for high temperature applications. Blocked rotor experiments and 3D finite element analyses reported show that the slitted-rotor SRM has lower core loss and higher torque density than the solid-rotor SRM. Further, mutually coupled winding connection is shown to enhance the torque output of both solid- and slitted-rotor SRMs, compared to conventional winding. Two new current control schemes are proposed in this research work. In the first part, an extended horizon model-based predictive current controller is proposed for SRM. An analytical equation is reported for real-time computation of the optimal duty ratio to minimize the RMS error between the future current references and predicted currents over a horizon. The proposed controller demonstrates lower RMS error in current tracking and robustness to parameter variations, with experimental validation on a laboratory prototype drive, over an existing dead-beat predictive controller. Further, a fixed-frequency, model-independent predictive current control for SRM is proposed. Unlike traditional approaches, this method does not require any pre-measured characteristics of the SRM. Instead, it only requires two constants: the optimal value of equivalent inductance and the moving average window period. Hence this method eliminates the need for time consuming characterization experiments, multi-dimensional lookup tables, and offline curve fitting to model the flux-linkage characteristics of the SRM for current control. A high-performance torque control scheme for SRMs is presented, incorporating a PI controller, feedforward compensation, high-frequency compensation, and optimized gating functions. This controller achieves significant reduction in pulsating torque and outperforms state-of-the-art techniques across various operating conditions. Further improvement in performance is achieved through a novel PWM-based optimal predictive direct torque control scheme. In this work, a cost function, encompassing the instantaneous torque error and the RMS values of phase currents is formulated to be minimized. An analytical expression for the optimal duty ratio towards this objective is derived resulting in improved computational efficiency. This controller delivers improved torque tracking, higher torque per ampere, and lower sound pressure levels compared to existing methods. An experimental method for determining the moment of inertia and frictional torque characteristics of SRMs is proposed. Using these identified parameters, a PI-based speed controller is designed and validated through simulations and experiments, demonstrating its effectiveness in enhancing the performance of SRM drives.