Active compressor stability management can play a significant role in the intelligent control of gas turbine engines. The present work utilizes a computer simulation to illustrate the potential operability benefits of compressor stability management when actively controlling a turbofan engine. The simulation, called the modular aeropropulsion system simulation (MAPSS) and developed at NASA Glenn, models the actuation, sensor, controller, and engine dynamics of a twin-spool, low-bypass turbofan engine. The stability management system is built around a previously developed stability measure called the correlation measure. The correlation measure quantifies the repeatability of the pressure signature of a compressor rotor. Earlier work has used laboratory compressor and engine rig data to develop a relationship between a compressor’s stability boundary and its correlation measure. Specifically, correlation measure threshold crossing events increase in magnitude and number as the compressor approaches the limit of stable operation. To simulate the experimentally observed behavior of these events, a stochastic model based on level-crossings of an exponentially distributed pseudorandom process has been implemented in the MAPSS environment. Three different methods of integrating active stability management within the existing engine control architecture have been explored. The results show that significant improvements in the engine emergency response can be obtained while maintaining instability-free compressor operation via any of the methods studied. Two of the active control schemes investigated utilize existing scheduler and controller parameters and require minimal additional control logic for implementation. The third method, while introducing additional logic, emphasizes the need for as well as the benefits of a more integrated stability management system.

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