ISBN: 978-981-14-4787-7 DOI: 10.18178/wcse.2020.06.058
Research on Multi-Objective Optimization of Control Parameters for Switched Reluctance Generators
Abstract— 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..
Index Terms— switched reluctance motor, differential evolution algorithm, multi-objective optimization, current ripple
Lei Dong, Qian Jiang, Lulu Ling, Liwei Shao
School of Automation, Beijing Institute of Technology,CHINA
Cite:Lei Dong, Qian Jiang, Lulu Ling, Liwei Shao " Research on Multi-Objective Optimization of Control Parameters for Switched Reluctance Generators " Proceedings of 2020 the 10th International Workshop on Computer Science and Engineering (WCSE 2020), pp.388-395, Shanghai, China, 19-21 June, 2020.