Yilmaz Sozer

A Fixed Switching Frequency Predictive Current Control Method for Switched Reluctance Machines

The paper presents a novel fixed switching frequency predictive current control method for switched reluctance machines (SRM). The proposed deadbeat predictive current controller accurately predicts the required duty ratio for the PWM pulse for a given reference current in each digital time step over the entire speed range of operation. The pulse width depends on the operating conditions, machine parameters and the rotor position. The controller utilizes the machine inductance profile as a function of current and rotor position to accurately predict the required voltage. The control method is studied through computer simulation and followed by experimental validation. The method is suitable for torque ripple sensitive applications requiring accurate tracking of a given current profile and mitigating the audible noise due to the switching of the inverter.

A Novel Load-Flow Analysis for Stable and Optimized Microgrid Operation

This paper proposes a novel load-flow analysis (LFA) algorithm for droop-based islanded microgrids (DBIM). The standard LFA is not applicable for DBIM due to the absence of a node with fixed reference voltage. As the voltage in the islanded microgrid depends on the droop relations, these relations are included as part of the load-flow equations. The proposed LFA is used with particle swarm optimization to select the droop parameters that optimize the reactive power sharing. Voltage compensation terms are also suggested to improve voltage regulation. By using the proposed LFA, a modeling procedure is suggested to check the stability and stabilize the microgrid. The effectiveness of the proposed methods is verified through different simulation studies.

Parallel Power Processing Topology for Solar PV Applications

A high efficiency converter topology for extracting maximum power from a photovoltaic (PV) module to charge standalone storage devices is presented in this paper. A reversed buck-boost converter enabling parallel power processing with a power switch referenced to the common return is the main core of the charging system. Small signal analysis of the proposed charging system is carried out to facilitate the design of a compensator for the maximum power point (MPP) tracking. The simulation and experimental results confirmed the validity of the model, and verified the high efficiency system operation with MPP tracking. The use of the PPP with the split loads is also presented, which would improve the size, efficiency and step down duty ratio of the converters.

A fixed switching frequency predictive current control method for switched reluctance machines

The paper presents a novel fixed switching frequency predictive current control method for switched reluctance machines (SRM). The proposed deadbeat predictive current controller accurately predicts the required amount of on-time for the PWM pulse for a given reference current in each digital time step over the entire speed range of operation. The required pulse width depends on the operating conditions, machine parameters and the rotor position. The controller utilizes the machine inductance profile as a function of current and rotor position to accurately predict the required voltage. The control method is studied through computer simulation and followed by experimental validation. The method is suitable for torque ripple sensitive applications requiring accurate tracking of a given current profile and mitigating the audible noise due to the switching of the inverter.

Power Flow Management of a Grid Tied PV-Battery System for Electric Vehicles Charging

The prospective spread of electric vehicles (EV) and plug-in hybrid EV raises the need for fast charging rates. High required charging rates lead to high power demands, which may not be supported by the grid. In this paper, an optimal power flow technique of a PV-battery powered fast EV charging station is presented to continuously minimize the operation cost. The objective is to help the penetration of PV-battery systems into the grid and to support the growing need of fast EV charging. An optimization problem is formulated along with the required constraints and the operating cost function is chosen as a combination of electricity grid prices and the battery degradation cost. In the first stage of the proposed optimization procedure, an offline particle swarm optimization (PSO) is performed as a prediction layer. In the second stage, dynamic programming (DP) is performed as an online reactive management layer. Forecasted system data is utilized in both stages to find the optimal power management solution. In the reactive management layer, the outputs of the PSO are used to limit the available state trajectories used in the DP and, accordingly, improve the system computation time and efficiency. Online error compensation is implemented into the DP and fed back to the prediction layer for necessary prediction adjustments. Simulation and 1 kW prototype experimental results are successfully implemented to validate the system effectiveness and to demonstrate the benefits of using a hybrid grid tied system of PV-battery for fast EVs charging stations.

Optimized Droop Control Parameters for Effective Load Sharing and Voltage Regulation in DC Microgrids

Abstract Droop control method is a widely used technique for achieving load sharing in DC microgrid applications. Virtual output impedance (or droop gain) and voltage reference are the main control parameters typically selected based on the power ratings of the sources for proper load sharing. The performance of droop controller is affected significantly by the voltage drops across the transmission line impedances, resulting in a load sharing error and voltage degradation across the microgrid. In this article, a new optimization procedure is proposed to find the optimal droop parameters such that the effect of the line impedances is minimized. An optimization problem along with the required constrains is formulated as the combination of current sharing errors as well as the voltage degradation for various loading conditions. Particle swarm-based technique is then used to provide a solution for this optimization problem. The performance of the droop controller with the optimal droop parameters is verified through a simulation case study implemented on the MATLAB/Simulink environment.

Maximum torque per ampere control for interior permanent magnet motors using DC link power measurement

Maximum torque per ampere (MTPA) control scheme for internal permanent magnet (IPM) machine is presented in this paper. Proposed control scheme was developed based on measurement of only DC link quantities eliminating the necessity of 3-phase current feedback. The scheme employs an online search algorithm with initial condition computed from a-priory system information. Hybridization of search based algorithm with pre-computed control coefficients ensures robustness against parameter variations while maintaining good dynamic performance.

Performance analysis of bi-directional DC-DC converters for electric vehicles and charging infrastructure

This paper presents the performance analysis and comparison of two different types of bidirectional DC-DC converters - Cascaded Buck-Boost (CBB) and Combined Half-Bridge (CHB) for use in Plug-in EV and HEV. The comparison of the two converters is based on device requirements, rating of switches and elements, control strategy and performance. Each of the converter topologies has some advantages over the other in certain aspects. Feasibility studies are carried for practical applications in specific scenarios. The simulation and experimental results are provided for both converter types to support the theoretical findings.

Plug-and-Play Nonlinear Droop Construction Scheme to Optimize Islanded Microgrid Operations

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Design considerations of a transverse flux machine for direct-drive wind turbine applications

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