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4. MATERIALS For an ultra-high-efficiency microturbine there is a need to evaluate and produce materials that will be able to withstand the operating conditions, especially the high temperatures. The materials properties (such as corrosion, oxidation, creep and strength) limit these temperatures (Figure 5). In the long term, the full performance of microturbines can probably only be achieved with ceramic materials. A candidate list of potential advanced materials up to now exists and future work will show the applicability and reliability of these materials. In order to fabricate components critical decisions have to be made. First the selection of the material that is best suitable and second the type of manufacture. A successful material candidate must include the following specifications: • low thermal expansion, • high thermal-shock resistance, • good corrosion and oxidation resistance, • high thermal strength, • good creep resistance, • ease to fabricate, and • low cost. 5. MODELLING, CONTROL AND FAULT DIAGNOSIS For the purpose of model-based control and fault detection a control oriented model (COM) is necessary [5]. A COM models the input-output behaviour of the micro gas turbine system with reasonable precision at low computational complexity. It is designed to include explicitly all relevant transient effects and is represented by a set of nonlinear ordinary differential equations, which are derived from physical first principles. Faults in a control loop of a micro gas turbine are particularly important since feedback from a faulty sensor or actor very Figure 5. The recuperator hot-gas inlet temperature determines materials selection. quickly result in instability causing a complete failure of the device. Such faults might need to be detected within just a few samples. Therefore it is important that faults are detected during normal operation of the gas turbine, without the need to perform any additional tests to perform the diagnosis. The gas turbine process is regulated by a controller and the known variables consist of controller outputs and sensor data. Such a situation is depicted in Figure 6, which also illustrates a fundamental complication faced by the diagnosis system designer. Disturbances, also called unknown inputs, and considered faults also influence the process. The diagnosis system must be capable of separating the influences caused by these unknown inputs and the faults. A certain redundancy is thus needed to detect and isolate faulty components. The detection and isolation of actuator as well as sensor failures will be done with the multiple model adaptive estimation method (MMAE). This algorithm is composed of a bank of parallel Kalman filters, each matched to a specific hypothesis about the failure status of the system. Where necessary, certain Kalman filters in the filter bank will be replaced by an extended Kalman filter [6]. 6. ELECTRICAL SYSTEM All gas turbine power supply systems require an electrical system consisting of a high-speed generator/starter, power electronics, a control platform and a form of energy storage to power the starting of the turbine. 6.1. Generator High-speed operation requires a simple and robust rotor geometry and construction. Therefore, a permanent-magnet machine has been chosen. The cylindrical permanent-magnet is encased in a retaining sleeve in order to limit the stresses on the brittle magnet. The eccentricity is minimized by shrink- fitting the sleeve on the permanent magnet and grinding the rotor. The rated speed is set in between two critical bending modes. Figure 6. Model-based and control-oriented diagnosis of the micro gas turbine.PDF Image | Ultra-High-Energy-Density Converter for Portable Power
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