Master of Science in Mechanical Engineering, Cleveland State University, 2021, Washkewicz College of Engineering

Recent developments in aircraft propulsion electrification are motivated by economic and environmental factors such as lowering greenhouse gas emissions, reducing noise, and increasing fuel efficiency. This thesis focuses on a hybrid gas-electric propulsion concept combining a gas turbine jet engine with an electromechanical (EM) system. An optimal control system allows energy to be recovered from the gas turbine engine or injected into it from an electric storage unit. Energy extraction or injection can be obtained by selecting a performance weight in the optimization function that trades off fuel consumption with stored electrical energy utilization. The goal of this research is to validate the effectiveness and plausibility of the optimal controller during representative acceleration and deceleration maneuvers and at steady state. To accomplish this, the gas turbine engine dynamics are simulated using NASA's T-MATS package and used in a hardware co-simulation approach along with physical hardware representative of the EM system, namely motors, power converter, and an energy storage device. A time scaling methodology was used to reconcile the power levels of the physical EM system (in the order of a kilowatt) with those of the engine simulation (in the order of megawatts). Multiple steady state missions were represented within a full simulation environment and in the lab test environment that covered a wide range of fuel-electric optimization weights. In addition, a chop-burst study was conducted to ensure the readiness of the system to handle flight missions. Based upon captured data, specifically that of shaft torque, supercapacitor voltage, and fuel flow measurements, it was determined that the optimal control objective was met. An increase in fuel-electric optimization weight corresponded to a desired change in torque to the engine and voltage to the energy storage device.

Committee: Hanz Richter (Advisor); Jerzy Sawicki (Committee Member); Lili Dong (Committee Member) Subjects: Engineering; Mechanical Engineering

Doctor of Engineering, Cleveland State University, 2017, Washkewicz College of Engineering

High Intensity Laser Power Beaming is a wireless power transmission technology developed at the Industrial Space Systems Laboratory from 2005 through 2010, in collaboration with the Air Force Research Laboratory to enable remote optical `refueling' of airborne electric micro unmanned air vehicles. Continuous tracking of these air vehicles with high intensity lasers while in-flight for tens of minutes to recharge the on-board battery system is not operationally practical; hence the recharge time must be minimized. This dissertation presents the development and system design optimization of a hybrid electrical energy storage system as a solution to this practical limitation. The solution is based on the development of a high energy density integrated system to capture and store pulsed energy. The system makes use of ultracapacitors to capture the energy at rapid charge rates, while lithium-ion batteries provide the long-term energy density, in order to maximize the duration of operations and minimize the mass requirements. A design tool employing a genetic algorithm global optimizer was developed to select the front-end ultracapacitor elements. The simulation model and results demonstrate the feasibility of the solution. The hybrid energy storage system is also optimized at the system-level for maximum end-to-end power transfer efficiency. System response optimization results and corresponding sensitivity analysis results are presented. Lastly, the ultrafast supply/extended energy storage system is generalized for other applications such as high-power commercial, industrial, and aerospace applications.

Committee: Hanz Richter Ph.D. (Committee Chair); Taysir Nayfeh Ph.D. (Committee Member); Lili Dong Ph.D. (Committee Member); Majid Rashidi Ph.D. (Committee Member); Petru Fodor Ph.D. (Committee Member) Subjects: Electrical Engineering