TY - JOUR
T1 - Multi-objective optimization of a tubular permanent magnet linear generator with 120° phase belt toroidal windings using response surface method and genetic algorithm
AU - Si, Jikai
AU - Yan, Zuoguang
AU - Nie, Rui
AU - Li, Zhongwen
AU - Hu, Yihua
AU - Li, Yingsheng
N1 - © 2021 The Authors. IET Renewable Power Generation published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology
PY - 2022/1/12
Y1 - 2022/1/12
N2 - In terms of the characteristics of multi-objective and interactions among optimization objectives of the tubular permanent magnet linear generator with 120° phase belt toroidal winding (120°-TPMLG), a multi-objective optimization method is proposed to improve the generators performances, which is based on the combination of response surface method and the genetic algorithm. First, the sensitivity analysis of different structural parameters on the performances of the 120°-TPMLG is conducted to pick out the sensitive structural parameters. Then develop those sensitive parameters as optimization variables to establish the response surface equation of the generator performances including output power (P), detent force (F), and the efficiency (η). Subsequently, based on the surface equation, the genetic algorithm (GA) fitness function is proposed to conducted the global optimization and the optimization results are finally obtained. To verify the effectiveness of the proposed optimization method, the performances of the optimal 120°-TPMLG are analysed and compared with the initial one. The results show that the performances including the detent force and power density of the 120°-TPMLG are greatly improved, which prove that the proposed multi-objective optimization method is effective for the 120°-TPMLG.
AB - In terms of the characteristics of multi-objective and interactions among optimization objectives of the tubular permanent magnet linear generator with 120° phase belt toroidal winding (120°-TPMLG), a multi-objective optimization method is proposed to improve the generators performances, which is based on the combination of response surface method and the genetic algorithm. First, the sensitivity analysis of different structural parameters on the performances of the 120°-TPMLG is conducted to pick out the sensitive structural parameters. Then develop those sensitive parameters as optimization variables to establish the response surface equation of the generator performances including output power (P), detent force (F), and the efficiency (η). Subsequently, based on the surface equation, the genetic algorithm (GA) fitness function is proposed to conducted the global optimization and the optimization results are finally obtained. To verify the effectiveness of the proposed optimization method, the performances of the optimal 120°-TPMLG are analysed and compared with the initial one. The results show that the performances including the detent force and power density of the 120°-TPMLG are greatly improved, which prove that the proposed multi-objective optimization method is effective for the 120°-TPMLG.
UR - http://www.scopus.com/inward/record.url?scp=85119335485&partnerID=8YFLogxK
U2 - 10.1049/rpg2.12328
DO - 10.1049/rpg2.12328
M3 - Article
AN - SCOPUS:85119335485
SN - 1752-1416
VL - 16
SP - 352
EP - 361
JO - IET Renewable Power Generation
JF - IET Renewable Power Generation
IS - 2
ER -