Study on Multi-objective Collaborative Optimization of Switched Reluctance Motor Based on Chaos Fruit Fly Optimization Algorithm

Authors

Xiaoping Zhang, 1. National-Local Joint Engineering Laboratory of Marine Mineral Resources Exploration Equipment and Safety Technology,Hunan University of Science and Technology, Xiangtan 411201, China;;
Shenghua Rao, 1. National-Local Joint Engineering Laboratory of Marine Mineral Resources Exploration Equipment and Safety Technology,Hunan University of Science and Technology, Xiangtan 411201, China;;
Zhang zhu, 2. College of Information and Electrical Engineering, Hunan University of Science and Technology, Xiangtan 411201, China;
Zhao xuan, 1. National-Local Joint Engineering Laboratory of Marine Mineral Resources Exploration Equipment and Safety Technology,Hunan University of Science and Technology, Xiangtan 411201, China;;

Abstract

Abstract: Switched reluctance motor (SRM) is difficult to get the best solution due to its complicated process and high professional requirement. Therefore, a collaborative multi-objective optimization method based on chaotic fruit fly algorithm is proposed in the paper. The initial solution is obtained by traditional design method, and the performance is verified by finite element analysis (FEA). The extreme learning machine (ELM) is applied to obtain the non-parameter model of SRM based on the sample data from FEA. The chaotic fruit fly algorithm is proposed for design optimization. Simulation results demonstrate that better coefficient of torque ripple and efficiency can be obtained, and it has the advantages of fewer parameters, faster convergence and is not easy to fall into local optimal solution. Moreover, better application value can be achieved.

Recommended Citation

Zhang, Xiaoping; Rao, Shenghua; zhu, Zhang; and xuan, Zhao (2019) "Study on Multi-objective Collaborative Optimization of Switched Reluctance Motor Based on Chaos Fruit Fly Optimization Algorithm," Journal of System Simulation: Vol. 30: Iss. 7, Article 26.
DOI: 10.16182/j.issn1004731x.joss.201807026
Available at: https://dc-china-simulation.researchcommons.org/journal/vol30/iss7/26

First Page

2640

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201807026

Last Page

2647

CLC

TM352

Recommended Citation

Zhang Xiaoping, Rao Shenghua, Zhang zhu, Zhao xuan. Study on Multi-objective Collaborative Optimization of Switched Reluctance Motor Based on Chaos Fruit Fly Optimization Algorithm[J]. Journal of System Simulation, 2018, 30(7): 2640-2647.

DOI

10.16182/j.issn1004731x.joss.201807026