Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/61228
Title: Maximum-force-per-Ampere strategy of current distribution for efficiency improvement in planar switched reluctance motors
Authors: Huang, SD
Cao, GZ
He, ZY
Wu, C
Duan, JA
Cheung, NC 
Qian, QQ
Keywords: Adaptive genetic algorithm
Efficiency improvement
Maximum force per ampere
Planar switched reluctance motor
Issue Date: 2016
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on industrial electronics, 2016, v. 63, no. 3, 7300440, p. 1665-1675 How to cite?
Journal: IEEE transactions on industrial electronics 
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.
URI: http://hdl.handle.net/10397/61228
ISSN: 0278-0046
EISSN: 1557-9948
DOI: 10.1109/TIE.2015.2492948
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