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|Title:||Multiobjective optimization of current waveforms for switched reluctance motors by genetic algorithm||Authors:||Xu, J.-X.
Switched reluctance motors
|Issue Date:||2004||Citation:||Xu, J.-X.,Panda, S.K.,Zheng, Q. (2004). Multiobjective optimization of current waveforms for switched reluctance motors by genetic algorithm. International Journal of Modelling and Simulation 24 (3) : 161-167. ScholarBank@NUS Repository.||Abstract:||In this article a genetic algorithm (GA) is employed to determine the desired current waveforms for switched reluctance motors (SRM) through generating appropriate reference phase torques for a given desired torque using torque-sharing function. The objective is to yield smoother phase current waveforms in general, and achieve minimum phase current variations in particular. This problem is formulated into a multiobjective optimization task with certain constraints. Due to the highly nonlinear relationship between the SRM torque and current, this optimization task is an NP-hard problem. To deal with the difficulty, the problem is further coded so that a GA can be applied to facilitate the search of global minimum. Simulation results verify the effectiveness of the proposed method.||Source Title:||International Journal of Modelling and Simulation||URI:||http://scholarbank.nus.edu.sg/handle/10635/56719||ISSN:||02286203|
|Appears in Collections:||Staff Publications|
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