Maximum-Force-per-Ampere Strategy of Current Distribution for Efficiency Improvement in Planar Switched Reluctance Motors

Su Dan Huang, Guang Zhong Cao, Zheng You He, Chao Wu, Ji An Duan, Chow Norbert Cheung, Qing Quan Qian

Research output: Journal article publicationJournal articleAcademic researchpeer-review

28 Citations (Scopus)

Abstract

This paper proposes a novel maximum-force-per-ampere strategy for the current distribution of planar switched reluctance motors (PSRMs) for efficiency improvement. This strategy is the first of its kind for planar motors, and it is used to generate the desired thrust force with the minimum sum of squares of the three-phase current. To formulate this strategy, a constrained optimization problem with time-varying parameters is first developed. Then, the problem is transformed into an unconstrained problem with a barrier function. Additionally, a self-designed adaptive genetic algorithm is introduced to solve the unconstrained optimization problem for locating the optimal currents. Comparative studies of the proposed and conventional strategies for a PSRM system are carried out via simulation and experiment, and planar trajectory tracking for the system with the proposed strategy is experimentally performed. The validity of the proposed strategy is also verified.
Original languageEnglish
Article number7300440
Pages (from-to)1665-1675
Number of pages11
JournalIEEE Transactions on Industrial Electronics
Volume63
Issue number3
DOIs
Publication statusPublished - 1 Mar 2016

Keywords

  • Adaptive genetic algorithm
  • efficiency improvement
  • maximum force per ampere
  • planar switched reluctance motor

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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