An Investigation of Switched Reluctance Rotor Position Estimation Using Neural Networks

Abstract

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.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1992
Accession Number
ADA252846

Entities

People

  • Jenifer M. Shannon

Organizations

  • Naval Air Warfare Center Aircraft Divison

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Acquisition
  • Aerial Warfare
  • Aircrafts
  • Computers
  • Computing System Architectures
  • Data Acquisition
  • Generators
  • Military Aircraft
  • Network Architecture
  • Networks
  • Neural Networks
  • Sawtooth Waveforms
  • Security
  • Standards
  • Transfer Functions
  • Vehicles
  • Warfare

Fields of Study

  • Physics

Readers

  • Electrical Engineering
  • Geodesy

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks