Integrated Design of Motor Drives Using Random Heuristic Optimization for Aerospace Applications

Benjamin Cheong, Paolo Giangrande, Patrick Wheeler, Pericle Zanchetta, Michael Galea

Research output: Journal PublicationConference articlepeer-review

1 Citation (Scopus)

Abstract

High power density for aerospace motor drives is a key factor in the successful realization of the More Electric Aircraft (MEA) concept. An integrated system design approach offers optimization opportunities, which could lead to further improvements in power density. However this requires multi-disciplinary modelling and the handling of a complex optimization problem that is discrete and nonlinear in nature. This paper proposes a multi-level approach towards applying random heuristic optimization to the integrated motor design problem. Integrated optimizations are performed independently and sequentially at different levels assigned according to the 4-level modelling paradigm for electric systems. This paper also details a motor drive sizing procedure, which poses as the optimization problem to solve here. Finally, results comparing the proposed multi-level approach with a more traditional single-level approach is presented for a 2.5 kW actuator motor drive design. The multi-level approach is found to be more computationally efficient than its counterpart.

Original languageEnglish
JournalSAE Technical Papers
Volume2017-September
DOIs
Publication statusPublished - 2017
EventSAE AeroTech Congress and Exhibition, AEROTECH 2017 - Fort Worth, United States
Duration: 26 Sept 201728 Sept 2017

ASJC Scopus subject areas

  • Automotive Engineering
  • Safety, Risk, Reliability and Quality
  • Pollution
  • Industrial and Manufacturing Engineering

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