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- All Subjects: Electric insulators and insulation
- All Subjects: Simulation
- All Subjects: Smart power grids
- Creators: Holbert, Keith E.
In this thesis, the main objective is to develop the control model of the Energy Management System (EMS). The energy and power management in the FREEDM system is digitally controlled therefore all signals containing system states are discrete. The EMS is modeled as a discrete closed loop transfer function in the z-domain. A breakdown of power and energy control devices such as EMS components may result in energy con-sumption error. This leads to one of the main focuses of the thesis which is to identify and study component failures of the designed control system. Moreover, H-infinity ro-bust control method is applied to ensure effectiveness of the control architecture. A focus of the study is cyber security attack, specifically bad data detection in price. Test cases are used to illustrate the performance of the EMS control design, the effect of failure modes and the application of robust control technique.
The EMS was represented by a linear z-domain model. The transfer function be-tween the pricing signal and the demand response was designed and used as a test bed. EMS potential failure modes were identified and studied. Three bad data detection meth-odologies were implemented and a voting policy was used to declare bad data. The run-ning mean and standard deviation analysis method proves to be the best method to detect bad data. An H-infinity robust control technique was applied for the first time to design discrete EMS controller for the FREEDM system.
The simulations consist of no radiation and radiation modeling. The no radiation modeling details the cell structure development and characterizes basic operations (read, erase and program) of a flash memory cell. The program time is observed to be approximately 10 μs while the erase time is approximately 0.1 ms.
The radiation modeling uses the fixed oxide charge method to analyze the TID effects on the same flash memory cell. After irradiation, a threshold voltage shift of the flash memory cell is observed. The threshold voltages of a programmed cell and an erased cell are reduced at an average rate of 0.025 V/krad.
The use of simulation techniques allows designers to better understand the TID response of a SST flash memory cell and to predict cell level TID effects without performing the costly in-situ irradiation experiments. The simulation and experimental results agree qualitatively. In particular, simulation results reveal that ‘0’ to ‘1’ errors but not ‘1’ to ‘0’ retention errors occur; likewise, ‘0’ to ‘1’ errors dominate experimental testing, which also includes circuitry effects that can cause ‘1’ to ‘0’ failures. Both simulation and experimental results reveal flash memory cell TID resilience to about 200 krad.
Currently, autonomous vehicles are being evaluated by how well they interact with humans without evaluating how well humans interact with them. Since people are not going to unanimously switch over to using autonomous vehicles, attention must be given to how well these new vehicles signal intent to human drivers from the driver’s point of view. Ineffective communication will lead to unnecessary discomfort among drivers caused by an underlying uncertainty about what an autonomous vehicle is or isn’t about to do. Recent studies suggest that humans tend to fixate on areas of higher uncertainty so scenarios that have a higher number of vehicle fixations can be reasoned to be more uncertain. We provide a framework for measuring human uncertainty and use the framework to measure the effect of empathetic vs non-empathetic agents. We used a simulated driving environment to create recorded scenarios and manipulate the autonomous vehicle to include either an empathetic or non-empathetic agent. The driving interaction is composed of two vehicles approaching an uncontrolled intersection. These scenarios were played to twelve participants while their gaze was recorded to track what the participants were fixating on. The overall intent was to provide an analytical framework as a tool for evaluating autonomous driving features; and in this case, we choose to evaluate how effective it was for vehicles to have empathetic behaviors included in the autonomous vehicle decision making. A t-test analysis of the gaze indicated that empathy did not in fact reduce uncertainty although additional testing of this hypothesis will be needed due to the small sample size.