Aeronautical Engineering: A continuing bibliography, supplement 120

This bibliography contains abstracts for 297 reports, articles, and other documents introduced into the NASA scientific and technical information system in February 1980

Aeronautical engineering: A continuing bibliography, supplement 122

This bibliography lists 303 reports, articles, and other documents introduced into the NASA scientific and technical information system in April 1980

Aeronautical Engineering: A special bibliography with indexes, supplement 55

This bibliography lists 260 reports, articles, and other documents introduced into the NASA scientific and technical information system in February 1975

Sensor failure detection system

Advanced concepts for detecting, isolating, and accommodating sensor failures were studied to determine their applicability to the gas turbine control problem. Five concepts were formulated based upon such techniques as Kalman filters and a screening process led to the selection of one advanced concept for further evaluation. The selected advanced concept uses a Kalman filter to generate residuals, a weighted sum square residuals technique to detect soft failures, likelihood ratio testing of a bank of Kalman filters for isolation, and reconfiguring of the normal mode Kalman filter by eliminating the failed input to accommodate the failure. The advanced concept was compared to a baseline parameter synthesis technique. The advanced concept was shown to be a viable concept for detecting, isolating, and accommodating sensor failures for the gas turbine applications

Aeronautical engineering: A special bibliography with indexes, supplement 80

This bibliography lists 277 reports, articles, and other documents introduced into the NASA scientific and technical information system in January 1977

Aeronautical Engineering: A special bibliography with indexes, supplement 64, December 1975

This bibliography lists 288 reports, articles, and other documents introduced into the NASA scientific and technical information system in November 1975

Aeronautical engineering: A special bibliography with indexes, supplement 82, April 1977

This bibliography lists 311 reports, articles, and other documents introduced into the NASA scientific and technical information system in March 1977

Aeronautical Engineering. A continuing bibliography, supplement 115

This bibliography lists 273 reports, articles, and other documents introduced into the NASA scientific and technical information system in October 1979

Non-linear model predictive energy management strategies for stand-alone DC microgrids

Due to substantial generation and demand fluctuations in stand-alone green micro-grids, energy management strategies (EMSs) are becoming essential for the power sharing purpose and regulating the microgrids voltage. The classical EMSs track the maximum power points (MPPs) of wind and PV branches independently and rely on batteries, as slack terminals, to absorb any possible excess energy. However, in order to protect batteries from being overcharged by realizing the constant current-constant voltage (IU) charging regime as well as to consider the wind turbine operational constraints, more flexible multivariable and non-linear strategies, equipped with a power curtailment feature, are necessary to control microgrids. This dissertation work comprises developing an EMS that dynamically optimises the operation of stand-alone dc microgrids, consisting of wind, photovoltaic (PV), and battery branches, and coordinately manage all energy flows in order to achieve four control objectives: i) regulating dc bus voltage level of microgrids; ii) proportional power sharing between generators as a local droop control realization; iii) charging batteries as close to IU regime as possible; and iv) tracking MPPs of wind and PV branches during their normal operations. Non-linear model predictive control (NMPC) strategies are inherently multivariable and handle constraints and delays. In this thesis, the above mentioned EMS is developed as a NMPC strategy to extract the optimal control signals, which are duty cycles of three DC-DC converters and pitch angle of a wind turbine. Due to bimodal operation and discontinuous differential states of batteries, microgrids belong to the class of hybrid dynamical systems of non-Filippov type. This dissertation work involves a mathematical approximation of stand-alone dc microgrids as complementarity systems (CSs) of Filippov type. The proposed model is used to develop NMPC strategies and to simulate microgrids using Modelica. As part of the modelling efforts, this dissertation work also proposes a novel algorithm to identify an accurate equivalent electrical circuit of PV modules using both standard test condition (STC) and nominal operating cell temperature (NOCT) information provided by manufacturers. Moreover, two separate stochastic models are presented for hourly wind speed and solar irradiance levels

Wind turbine simulator fault diagnosis via fuzzy modelling and identification techniques

For improving the safety and the reliability of wind turbine installations, the earliest and fastest fault detection and isolation are highly required, since it could be used also for accommodation purpose. Modern wind turbines consist of several important subsystems, which can be affected by malfunctions regarding actuators, sensors, and components. From the turbine control point-of-view they are extremely important since provide the actuation signals, the main functions, as well as the measurements. In this paper, a fault diagnosis scheme based on the identification of fuzzy models is described, in order to detect and isolate these faults in the most efficient way, in order also to improve the energy cost, the production rate, and reduce the operation and maintenance operations. Fuzzy systems are proposed here since the model under investigation is nonlinear, whilst the wind speed measurement is uncertain since it depends on the rotor plane wind turbulence effects. These fuzzy models are described as Takagi-Sugeno prototypes, whose parameters are estimated from the wind turbine measurements. The fault diagnosis methodology is thus developed using these fuzzy models, which are exploited as residual generators. The wind turbine simulator is finally employed for the validation of the obtained performances.For improving the safety and the reliability of wind turbine installations, the earliest and fastest fault detection and isolation is highly required, since it could be used also for accommodation purpose. Modern wind turbines consist of several important subsystems, which can be affected by malfunctions regarding actuators, sensors, and components. From the turbine control point–of–view they are extremely important since provide the actuation signals, the main functions, as well as the measurements. In this paper, a fault diagnosis scheme based on the identification of fuzzy models is described, in order to detect and isolated these faults in the most efficient way, in order also to improve the energy cost, the production rate, and reduce the operation and maintenance operations. Fuzzy systems are proposed here since the model under investigation is nonlinear, whilst the wind speed measurement is uncertain since it depends on the rotor plane wind turbulence effects. These fuzzy models are described as Takagi–Sugeno prototypes, whose parameters are estimated from the wind turbine measurements. The fault diagnosis methodology is thus developed using these fuzzy models, which are exploited as residual generators. The wind turbine simulator is finally employed for the validation of the obtained performances