Publication Detail

Quarterly Report On the Contributions from MIT to the Electric Ship Research and Development Consortium, October-December, 2008

Chryssostomos Chryssostomidis, Franz Hover, George Em Karniadakis
45 pp.

We have developed a new computational framework consisted of detailed models for the two primary components of the All-Electric Ship (AES), namely Integrated Power System (IPS) and Hydrodynamics. This is the first time that all components of each system have been modeled and coupled together at this level. Simulating such a coupled system on today's computers is feasible, and results can be obtained in a matter of minutes even for long-time integration of the system to include the characteristic electric, mechanical and hydrodynamic scales. We note that these characteristic time scales, even of the small subcomponents, are not input to the problem but they are part of the solution, unlike other models where simplified lumped parameterizations are employed. This new computational framework is applied to a model of the DDG-51 destroyer that involves a 19 MW 15-phase induction machine (IM) and an indirect field oriented controller (IFOC). In particular, we simulate the extreme event of propeller emergence.

We investigate the robustness of integrated power system layouts from a network theoretic perspective. We find that an abstracted electric ship model based on a notional cruiser line diagram behaves more like an Erdos-Renyi random network than a scale-free network, and furthermore that scale-free networks are significantly less robust than random and notational cruiser-type networks, under the loading and failure conditions considered. A second area of research has been particle filtering. Specifically, we apply stochastic collocation, a tool we previously used for uncertainty analysis in the AES, to make sampling from proposal distributions more efficient, and hence increase the real-time applicability of particle filters.

Our efforts this past quarter focused on the design and evaluation of motors to match reported specifications and performance for two different Alstom machines, a 19 MW, up to 150 RPM, motor and a 20 MW, up to 180 RPM, design. An IEEE paper, “The Advanced Induction Motor,” by Clive Lewis from the 2002 IEEE Power Engineering Society Summer Meeting describes both machines. As a physically realizable design, previously built and tested, the 19 MW machine provides a baseline for verifying the MIT motor evaluation software on a low speed, multi-megawatt motor as well as a realistic framework for examining design modifications. The initial designs were also altered for comparison with two different cases, first doubling the initial motor power output, speed, and frequency, and second doubling the speed and frequency while maintaining the original power output but with a reduced motor size and weight. After designing around the full load operating points, changes in motor efficiency with varying speed and corresponding load were also compared between designs.

Power system monitoring is an exciting approach for creating an inexpensive, highly capable “black-box” for monitoring the performance of critical shipboard systems. With remarkably little installation effort or expense, we have fielded a non-intrusive load monitor (NILM) that can reliably monitor and track diagnostic conditions for multiple devices. During the past quarter, we have worked to automate the recognition of load operation and diagnostic monitoring to make results available to the crew in real-time. To do so, we have developed a software package known as ginzu that eliminates the need for off-line analysis by a skilled observer. Initial tracking of load operation and diagnostic condition are now provided automatically by the NILM on-board ship. Furthermore, our field-tested systems have been installed at a central point that allows them to monitor multiple loads simultaneously. The ginzu software application implements a detect-classify-verify loop that locates electrical load transients, identifies them using a decision-tree-based expert classifier, and then generates event files that contain relevant information. Additionally, the ginzu application provides streaming data to a graphical user interface known as the Ginzu Graphical User Interface (GinzUI)

We developed robust models for ship hydrodynamics, including forward propulsion and maneuvering, as well as models for the propeller and the linear and nonlinear loads in a random sea-state; models for the gas turbine, generator, electric system, and motor. The models were developed at various levels of accuracy so as to assess the principal time constants and parameters of the system, and thorough testing of the power flow and transient dynamics was made. Controllers for the gas turbine, generator and motor were developed and tested. This led to a system that can be parameterized in terms of the significant parameters so as to perform sensitivity analysis and stochastic simulation. Simulations that involve random loads from the sea, random events such as propeller emergence, and maneuvering motions in a storm are possible with the models developed. Sensitivity tables exhibiting the parameter to parameter finite-amplitude sensitivity have been developed that allow time-varying assessment of the critical parameters.

type: Technical reports

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Parent Project

Project No.: 2008-ESRDC-01-LEV
Title: Electric Ship Research and Development Consortium (ESRDC)

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