TY - GEN
T1 - Research on multi-objective optimization of control parameters for switched reluctance generators
AU - Dong, Lei
AU - Jiang, Qian
AU - Ling, Lulu
AU - Shao, Liwei
N1 - Publisher Copyright:
© WCSE 2020.
PY - 2020
Y1 - 2020
N2 - This paper presents a power generation control parameter optimization model of switched reluctance motor based on differential evolution algorithm. In order to find the solution, the linear weighting method is used to transform the multi-objective optimization problem into a single-objective optimization problem, and then the differential evolution algorithm is used to search the optimal solution of single-objective optimization. Matlab/Simulink was used to build the multi-objective optimization model of switched reluctance motor to study the effect of the turn-on angle, the freewheeling angle, the turn-off angle on the output power, generation efficiency and DC terminal current ripple under Freewheeling Control Method to find the commutation angle that can make all performance indexes reach the optimal at the same time at different rotational speeds.
AB - This paper presents a power generation control parameter optimization model of switched reluctance motor based on differential evolution algorithm. In order to find the solution, the linear weighting method is used to transform the multi-objective optimization problem into a single-objective optimization problem, and then the differential evolution algorithm is used to search the optimal solution of single-objective optimization. Matlab/Simulink was used to build the multi-objective optimization model of switched reluctance motor to study the effect of the turn-on angle, the freewheeling angle, the turn-off angle on the output power, generation efficiency and DC terminal current ripple under Freewheeling Control Method to find the commutation angle that can make all performance indexes reach the optimal at the same time at different rotational speeds.
KW - Current ripple
KW - Differential evolution algorithm
KW - Multi-objective optimization
KW - Switched reluctance motor
UR - http://www.scopus.com/inward/record.url?scp=85092415587&partnerID=8YFLogxK
U2 - 10.18178/wcse.2020.06.058
DO - 10.18178/wcse.2020.06.058
M3 - Conference contribution
AN - SCOPUS:85092415587
T3 - WCSE 2020: 2020 10th International Workshop on Computer Science and Engineering
SP - 388
EP - 395
BT - WCSE 2020
PB - International Workshop on Computer Science and Engineering (WCSE)
T2 - 2020 10th International Workshop on Computer Science and Engineering, WCSE 2020
Y2 - 19 June 2020 through 21 June 2020
ER -