The Switched Reluctance Machine (SRM) has potential applications in the More-Electric Aircraft program. Such applications include fuel and oil pump, actuators, braking systems and integral starter/generators. However, one difficulty in the controller design still exists. Knowledge of the relative position of the rotor with the stator is required for timing of the excitation pulses. This position is conventionally measured by an encoder or resolver. However, for many applications of the SRM such a sensor will not operate in the harsh environment of the machine. Developing a means of estimating the rotor position without the need for a rotor-mounted position sensor is the aim of this research. Specifically, this paper investigates the possibility of using neural networks for rotor position estimation.
Investigation of Switched Reluctance Rotor Position Estimation Using Neural Networks
1992
19 pages
Report
No indication
English
Aircraft , Jet & Gas Turbine Engines , Circuits , Rotors , Position(Location) , Neural nets , Actuators , Braking , Coders , Environments , Excitation , Fuels , Generators , Integrals , Machines , Networks , Oils , Pulses , Pumps , Stators , Control systems , Switching , Aircraft engines , Back propagation
A Switched Reluctance Machine Rotor Position Estimator: A Neural Network Application
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