This document compares two measurement methods for the determination of extended turbine maps. One method is to minimize heat flows and thus to maintain the assumption of adiabatic processes even in low speed ranges of turbines. The results obtained were compared with those of the Ostfalia eATL method. Here, is slowed down electrically by an electric motor. The direct comparison of the measurement results shows considerable differences in the turbine efficiency. Furthermore, the graphical comparison illustrates clear advantages of the eATL concept for the evaluation, which result from the width and the position of the generated measurement points.
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This paper compares two different approaches to the construction of Takagi-Sugeno fuzzy models from data. These models approximate nonlinear systems by means of interpolation between local linear models. The main issue in the construction of Takagi-Sugeno models is the decomposition of the operating space into validity regions for the local models. The way this decomposition is done influences the complexity, accuracy and transparency of the obtained model. The first of the presented methods, the local linear model tree (LOLIMOT) algorithm generates incrementally the fuzzy model by axis-orthogonal decomposition of the input space. In the other method, product-space fuzzy clustering (the Gustafson-Kessel algorithm) is used to partition the available data into fuzzy subsets. The fundamental advantages and drawbacks of both the alternative strategies are pointed out. Their properties and real-world applicability are illustrated by building a dynamic model of a truck Diesel engine turbocharger.
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