A Switched Reluctance Machine Rotor Position Estimator: A Neural Network Application

Paper #:
  • 932560

Published:
  • 1993-09-01
Citation:
Shannon, J., "A Switched Reluctance Machine Rotor Position Estimator: A Neural Network Application," SAE Technical Paper 932560, 1993, https://doi.org/10.4271/932560.
Author(s):
Pages:
10
Abstract:
A method of estimating the rotor position of a switched reluctance machine without the need for a rotor-mounted position sensor has been developed. This method takes advantage of the information derived from known phase voltage and current waveforms. The information is fed as the inputs to a neural network, which after being trained, can correctly map the rotor position to its output. The most accurate mapping results were obtained using a Cerebellar Model Articulation Controller (CMAC) neural network. The performance of the neural network has been tested with measured waveforms from a three phase 120 HP switched reluctance motor. It successfully maps the rotor position with an average root mean square error of one tenth of a mechanical degree.
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