ANN Based Magnetic Field and Inductance Modeling of Double Sided Linear Switched Reluctance Motor


Ozden S., Manav G., DURSUN M.

5th International Conference on Electrical and Electronics Engineering (ICEEE), İstanbul, Turkey, 3 - 05 May 2018, pp.133-137 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/iceee2.2018.8391316
  • City: İstanbul
  • Country: Turkey
  • Page Numbers: pp.133-137
  • Keywords: component, linear motor, switched reluctance motor, inductance modelling, artificial neural network, RIPPLE MINIMIZATION, SYSTEM
  • Gazi University Affiliated: Yes

Abstract

In this study, ANN based magnetic field modeling has been experimentally achieved for Double Sided Linear Switched Reluctance Motor (DLSRM) with 6/4 poles, 3 phases, 250W. Inductance modeling profile overlaps magnetic field data was obtained from hall-effect sensor. It is important that estimation inductance value against phase current and motor position due to main factors of the propulsion force. The precise inductance modeling helps to overcome DLSRM nonlinearity characteristic. In addition, the model is useful for controlling motor such as adaptive control methods, new developed force control methods, position control without sensor to be able removing some parts and becoming simplicity of control algorithms.