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Integrated design of motor drives using random heuristic optimization for aerospace applications

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

Authors

Benjamin Cheong

Paolo Giangrande

MICHAEL GALEA Michael.Galea@nottingham.ac.uk
Professor of Electrical Machines and Drives



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 non┬Člinear 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.

Citation

Cheong, B., Giangrande, P., Galea, M., Zanchetta, P., & Wheeler, P. (2017). Integrated design of motor drives using random heuristic optimization for aerospace applications.

Conference Name SAE AeroTech Congress and Exhibition, AEROTECH 2017
End Date Sep 28, 2017
Acceptance Date Jul 18, 2017
Publication Date Sep 9, 2017
Deposit Date Nov 15, 2017
Publicly Available Date Nov 15, 2017
Peer Reviewed Peer Reviewed
Public URL https://nottingham-repository.worktribe.com/output/881528
Publisher URL http://papers.sae.org/2017-01-2030/

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